103,201 results
Search Results
2. Exploring the potential of artificial intelligence to enhance the writing of english academic papers by non-native english-speaking medical students - the educational application of ChatGPT.
- Author
-
Li J, Zong H, Wu E, Wu R, Peng Z, Zhao J, Yang L, Xie H, and Shen B
- Subjects
- Humans, China, Education, Medical, Undergraduate, Male, Female, Language, Writing, Students, Medical, Artificial Intelligence
- Abstract
Background: Academic paper writing holds significant importance in the education of medical students, and poses a clear challenge for those whose first language is not English. This study aims to investigate the effectiveness of employing large language models, particularly ChatGPT, in improving the English academic writing skills of these students., Methods: A cohort of 25 third-year medical students from China was recruited. The study consisted of two stages. Firstly, the students were asked to write a mini paper. Secondly, the students were asked to revise the mini paper using ChatGPT within two weeks. The evaluation of the mini papers focused on three key dimensions, including structure, logic, and language. The evaluation method incorporated both manual scoring and AI scoring utilizing the ChatGPT-3.5 and ChatGPT-4 models. Additionally, we employed a questionnaire to gather feedback on students' experience in using ChatGPT., Results: After implementing ChatGPT for writing assistance, there was a notable increase in manual scoring by 4.23 points. Similarly, AI scoring based on the ChatGPT-3.5 model showed an increase of 4.82 points, while the ChatGPT-4 model showed an increase of 3.84 points. These results highlight the potential of large language models in supporting academic writing. Statistical analysis revealed no significant difference between manual scoring and ChatGPT-4 scoring, indicating the potential of ChatGPT-4 to assist teachers in the grading process. Feedback from the questionnaire indicated a generally positive response from students, with 92% acknowledging an improvement in the quality of their writing, 84% noting advancements in their language skills, and 76% recognizing the contribution of ChatGPT in supporting academic research., Conclusion: The study highlighted the efficacy of large language models like ChatGPT in augmenting the English academic writing proficiency of non-native speakers in medical education. Furthermore, it illustrated the potential of these models to make a contribution to the educational evaluation process, particularly in environments where English is not the primary language., (© 2024. The Author(s).)
- Published
- 2024
- Full Text
- View/download PDF
3. Artificial Intelligence in the Provision of Health Care: An American College of Physicians Policy Position Paper.
- Author
-
Daneshvar N, Pandita D, Erickson S, Snyder Sulmasy L, and DeCamp M
- Subjects
- Humans, United States, Confidentiality, Electronic Health Records, Societies, Medical, Delivery of Health Care standards, Internal Medicine, Health Policy, Patient-Centered Care standards, Machine Learning, Artificial Intelligence, Physician-Patient Relations
- Abstract
Internal medicine physicians are increasingly interacting with systems that implement artificial intelligence (AI) and machine learning (ML) technologies. Some physicians and health care systems are even developing their own AI models, both within and outside of electronic health record (EHR) systems. These technologies have various applications throughout the provision of health care, such as clinical documentation, diagnostic image processing, and clinical decision support. With the growing availability of vast amounts of patient data and unprecedented levels of clinician burnout, the proliferation of these technologies is cautiously welcomed by some physicians. Others think it presents challenges to the patient-physician relationship and the professional integrity of physicians. These dispositions are understandable, given the "black box" nature of some AI models, for which specifications and development methods can be closely guarded or proprietary, along with the relative lagging or absence of appropriate regulatory scrutiny and validation. This American College of Physicians (ACP) position paper describes the College's foundational positions and recommendations regarding the use of AI- and ML-enabled tools and systems in the provision of health care. Many of the College's positions and recommendations, such as those related to patient-centeredness, privacy, and transparency, are founded on principles in the ACP Ethics Manual. They are also derived from considerations for the clinical safety and effectiveness of the tools as well as their potential consequences regarding health disparities. The College calls for more research on the clinical and ethical implications of these technologies and their effects on patient health and well-being., Competing Interests: Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M24-0146.
- Published
- 2024
- Full Text
- View/download PDF
4. In Context: AI Will Write Your Paper: The Very Different Future of Research and Scientific Writing in the Age of Artificial Intelligence.
- Author
-
Javanbakht A
- Subjects
- Humans, Writing, Biomedical Research standards, Artificial Intelligence
- Abstract
Plain Language Summary: In this article, the author reflects upon recent advancements in artificial intelligence (AI) technologies have led to profound discussions about AI's role in scientific research and education. AI technologies are now capable of summarizing and analyzing large volumes of data, creating presentations, and even drafting parts of scientific papers and grants with minimal human input. With their exponential ongoing advancements, they will become even more capable in doing these tasks. As boundaries between humans and AI blurs, serious questions arise about the future roles, responsibilities, and identity of academic researchers, intellectual property, publishing and grantsmanship, and equity in the world of AI potentiated research., (Copyright © 2024 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.)
- Published
- 2024
- Full Text
- View/download PDF
5. Digital Twins and the Terminology of 'Personalization' or 'Personalized Learning' in Educational Policy: A Discussion Paper
- Author
-
Janine Arantes
- Abstract
There has been a policy push in K-12 educational settings towards personalized learning in the last decade. Commercial platforms and learning designers have responded, offering learning tools to support teaching and learning through data-driven insights and recommendations. Trending towards the augmentation or replacing human teachers with non-human technology, this paper argues that personalized learning with human teachers is an entirely different process from personalization with digital twins. Drawing on new materialist thinking, it explores the impacts and implications for discourse concerning teacher quality and disadvantages within educational systems. It clarifies the conflation of the terms "personalized learning" and "personalization" to illuminate the power, positionality, and privilege enabled for some, in conflating terms in Australian educational policy.
- Published
- 2024
- Full Text
- View/download PDF
6. The 100 most influential papers in medical artificial intelligence; a bibliometric analysis.
- Author
-
Zahoor F, Abdullah M, Tahir MW, and Islam A
- Subjects
- Humans, Periodicals as Topic statistics & numerical data, Artificial Intelligence, Bibliometrics, Clinical Medicine
- Abstract
Objective: To assess the current trends in the field of artificial intelligence in medicine by analysing 100 most cited original articles relevant to the field., Methods: The bibliometric analysis was conducted in September 2022, and comprised literature search on Scopus database for original articles only. Google and Medical Subject Headings databases were used as resources to extract key words. In order to cover a broad range of articles, original studies comprising human as well as non-human subjects, studies without abstract and studies in languages other than English were part of the inclusion criteria. There was no specific time period applied to the search and no specific selection was done regarding the journals in the database. The screening was done using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to extract the top 100 most cited articles in the field of artificial intelligence usage in medicine. Data was analysed using SPSS 23., Results: Of the 11,571 studies identified, 100(0.86%) were analysed in detail. The studies were published between 1986 and 2021, with a median of 43 citations (IQR 53) per article. The journal 'Artificial Intelligence in Medicine' accounted for the highest number 9(9%)) of articles, and the United States was the country of origin for most of the articles 36(36%)., Conclusion: The trends, development and shortcomings in field of artificial intelligence usage in medicine need to be understood to conduct an effective research in areas that still need attention, and to guide the authorities to direct their funding accordingly.
- Published
- 2024
- Full Text
- View/download PDF
7. Digital cytology part 2: artificial intelligence in cytology: a concept paper with review and recommendations from the American Society of Cytopathology Digital Cytology Task Force.
- Author
-
Kim D, Sundling KE, Virk R, Thrall MJ, Alperstein S, Bui MM, Chen-Yost H, Donnelly AD, Lin O, Liu X, Madrigal E, Michelow P, Schmitt FC, Vielh PR, Zakowski MF, Parwani AV, Jenkins E, Siddiqui MT, Pantanowitz L, and Li Z
- Subjects
- Humans, Cytological Techniques, Laboratories, Workflow, Artificial Intelligence, Cytodiagnosis
- Abstract
Digital cytology and artificial intelligence (AI) are gaining greater adoption in the cytology laboratory. However, peer-reviewed real-world data and literature are lacking in regard to the current clinical landscape. The American Society of Cytopathology in conjunction with the International Academy of Cytology and the Digital Pathology Association established a special task force comprising 20 members with expertise and/or interest in digital cytology. The aim of the group was to investigate the feasibility of incorporating digital cytology, specifically cytology whole slide scanning and AI applications, into the workflow of the laboratory. In turn, the impact on cytopathologists, cytologists (cytotechnologists), and cytology departments were also assessed. The task force reviewed existing literature on digital cytology, conducted a worldwide survey, and held a virtual roundtable discussion on digital cytology and AI with multiple industry corporate representatives. This white paper, presented in 2 parts, summarizes the current state of digital cytology and AI practice in global cytology practice. Part 1 of the white paper is presented as a separate paper which details a review and best practice recommendations for incorporating digital cytology into practice. Part 2 of the white paper presented here provides a comprehensive review of AI in cytology practice along with best practice recommendations and legal considerations. Additionally, the cytology global survey results highlighting current AI practices by various laboratories, as well as current attitudes, are reported., (Copyright © 2023 American Society of Cytopathology. Published by Elsevier Inc. All rights reserved.)
- Published
- 2024
- Full Text
- View/download PDF
8. Digital cytology part 1: digital cytology implementation for practice: a concept paper with review and recommendations from the American Society of Cytopathology Digital Cytology Task Force.
- Author
-
Kim D, Sundling KE, Virk R, Thrall MJ, Alperstein S, Bui MM, Chen-Yost H, Donnelly AD, Lin O, Liu X, Madrigal E, Michelow P, Schmitt FC, Vielh PR, Zakowski MF, Parwani AV, Jenkins E, Siddiqui MT, Pantanowitz L, and Li Z
- Subjects
- Humans, Cytological Techniques, Laboratories, Workflow, Artificial Intelligence, Cytodiagnosis
- Abstract
Digital cytology and artificial intelligence (AI) are gaining greater adoption in the cytopathology laboratory. However, peer-reviewed real-world data and literature are lacking regarding the current clinical landscape. The American Society of Cytopathology in conjunction with the International Academy of Cytology and the Digital Pathology Association established a special task force comprising 20 members with expertise and/or interest in digital cytology. The aim of the group was to investigate the feasibility of incorporating digital cytology, specifically cytology whole slide scanning and AI applications, into the workflow of the laboratory. In turn, the impact on cytopathologists, cytologists (cytotechnologists), and cytology departments were also assessed. The task force reviewed existing literature on digital cytology, conducted a worldwide survey, and held a virtual roundtable discussion on digital cytology and AI with multiple industry corporate representatives. This white paper, presented in 2 parts, summarizes the current state of digital cytology and AI practice in global cytology practice. Part 1 of the white paper presented herein is a review and offers best practice recommendations for incorporating digital cytology into practice. Part 2 of the white paper provides a comprehensive review of AI in cytology practice along with best practice recommendations and legal considerations. Additionally, the results of a global survey regarding digital cytology are highlighted., (Copyright © 2023 American Society of Cytopathology. Published by Elsevier Inc. All rights reserved.)
- Published
- 2024
- Full Text
- View/download PDF
9. Is Artificial Intelligence Really the next Big Thing in Learning and Teaching in Higher Education? A Conceptual Paper
- Author
-
O'Dea, Xianghan and O'Dea, Mike
- Abstract
Artificial Intelligence in higher education (AIED) is becoming a more important research area with increasing developments and application of AI within the wider society. However, as yet AI based tools have not been widely adopted in higher education. As a result there is a lack of sound evidence available on the pedagogical impact of AI for learning and teaching. This conceptual paper thus seeks to bridge the gap and addresses the following question: is artificial intelligence really the new big thing that will revolutionise learning and teaching in higher education? Adopting the technological pedagogical content knowledge (TPACK) framework and the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical foundations, we argue that Artificial Intelligence (AI) technologies, at least in their current state of development, do not afford any real new advances for pedagogy in higher education. This is mainly because there does not seem to be valid evidence as to how the use of AI technologies and applications has helped students improve learning, and/or helped tutors make effective pedagogical changes. In addition, the pedagogical affordances of AI have not yet been clearly defined. The challenges that the higher education sector is currently experiencing relating to AI adoption are discussed at three hierarchical levels, namely national, institutional and personal levels. The paper ends with recommendations with regard to accelerating AI use in universities. This includes developing dedicated AI adoption strategies at the institutional level, updating the existing technology infrastructure and upskilling academic tutors for AI.
- Published
- 2023
10. The ChatGPT effect and transforming nursing education with generative AI: Discussion paper.
- Author
-
Gosak L, Pruinelli L, Topaz M, and Štiglic G
- Subjects
- Humans, Nursing Diagnosis, Documentation, Educational Status, Artificial Intelligence, Education, Nursing
- Abstract
Aim: The aim of this study is to present the possibilities of nurse education in the use of the Chat Generative Pre-training Transformer (ChatGPT) tool to support the documentation process., Background: The success of the nursing process is based on the accuracy of nursing diagnoses, which also determine nursing interventions and nursing outcomes. Educating nurses in the use of artificial intelligence in the nursing process can significantly reduce the time nurses spend on documentation., Design: Discussion paper., Methods: We used a case study from Train4Health in the field of preventive care to demonstrate the potential of using Generative Pre-training Transformer (ChatGPT) to educate nurses in documenting the nursing process using generative artificial intelligence. Based on the case study, we entered a description of the patient's condition into Generative Pre-training Transformer (ChatGPT) and asked questions about nursing diagnoses, nursing interventions and nursing outcomes. We further synthesized these results., Results: In the process of educating nurses about the nursing process and nursing diagnosis, Generative Pre-training Transformer (ChatGPT) can present potential patient problems to nurses and guide them through the process from taking a medical history, setting nursing diagnoses and planning goals and interventions. Generative Pre-training Transformer (ChatGPT) returned appropriate nursing diagnoses, but these were not in line with the North American Nursing Diagnosis Association - International (NANDA-I) classification as requested. Of all the nursing diagnoses provided, only one was consistent with the most recent version of the North American Nursing Diagnosis Association - International (NANDA-I). Generative Pre-training Transformer (ChatGPT) is still not specific enough for nursing diagnoses, resulting in incorrect answers in several cases., Conclusions: Using Generative Pre-training Transformer (ChatGPT) to educate nurses and support the documentation process is time-efficient, but it still requires a certain level of human critical-thinking and fact-checking., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)
- Published
- 2024
- Full Text
- View/download PDF
11. Automated Paper Screening for Clinical Reviews Using Large Language Models: Data Analysis Study.
- Author
-
Guo E, Gupta M, Deng J, Park YJ, Paget M, and Naugler C
- Subjects
- Humans, Consensus, Data Analysis, Problem Solving, Natural Language Processing, Workflow, Biomedical Research, Systematic Reviews as Topic, Artificial Intelligence
- Abstract
Background: The systematic review of clinical research papers is a labor-intensive and time-consuming process that often involves the screening of thousands of titles and abstracts. The accuracy and efficiency of this process are critical for the quality of the review and subsequent health care decisions. Traditional methods rely heavily on human reviewers, often requiring a significant investment of time and resources., Objective: This study aims to assess the performance of the OpenAI generative pretrained transformer (GPT) and GPT-4 application programming interfaces (APIs) in accurately and efficiently identifying relevant titles and abstracts from real-world clinical review data sets and comparing their performance against ground truth labeling by 2 independent human reviewers., Methods: We introduce a novel workflow using the Chat GPT and GPT-4 APIs for screening titles and abstracts in clinical reviews. A Python script was created to make calls to the API with the screening criteria in natural language and a corpus of title and abstract data sets filtered by a minimum of 2 human reviewers. We compared the performance of our model against human-reviewed papers across 6 review papers, screening over 24,000 titles and abstracts., Results: Our results show an accuracy of 0.91, a macro F
1 -score of 0.60, a sensitivity of excluded papers of 0.91, and a sensitivity of included papers of 0.76. The interrater variability between 2 independent human screeners was κ=0.46, and the prevalence and bias-adjusted κ between our proposed methods and the consensus-based human decisions was κ=0.96. On a randomly selected subset of papers, the GPT models demonstrated the ability to provide reasoning for their decisions and corrected their initial decisions upon being asked to explain their reasoning for incorrect classifications., Conclusions: Large language models have the potential to streamline the clinical review process, save valuable time and effort for researchers, and contribute to the overall quality of clinical reviews. By prioritizing the workflow and acting as an aid rather than a replacement for researchers and reviewers, models such as GPT-4 can enhance efficiency and lead to more accurate and reliable conclusions in medical research., (©Eddie Guo, Mehul Gupta, Jiawen Deng, Ye-Jean Park, Michael Paget, Christopher Naugler. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 12.01.2024.)- Published
- 2024
- Full Text
- View/download PDF
12. Rising adoption of artificial intelligence in scientific publishing: evaluating the role, risks, and ethical implications in paper drafting and review process.
- Author
-
Carobene A, Padoan A, Cabitza F, Banfi G, and Plebani M
- Subjects
- Humans, Benchmarking, Research Personnel, Artificial Intelligence, Publishing
- Abstract
Background: In the rapid evolving landscape of artificial intelligence (AI), scientific publishing is experiencing significant transformations. AI tools, while offering unparalleled efficiencies in paper drafting and peer review, also introduce notable ethical concerns., Content: This study delineates AI's dual role in scientific publishing: as a co-creator in the writing and review of scientific papers and as an ethical challenge. We first explore the potential of AI as an enhancer of efficiency, efficacy, and quality in creating scientific papers. A critical assessment follows, evaluating the risks vs. rewards for researchers, especially those early in their careers, emphasizing the need to maintain a balance between AI's capabilities and fostering independent reasoning and creativity. Subsequently, we delve into the ethical dilemmas of AI's involvement, particularly concerning originality, plagiarism, and preserving the genuine essence of scientific discourse. The evolving dynamics further highlight an overlooked aspect: the inadequate recognition of human reviewers in the academic community. With the increasing volume of scientific literature, tangible metrics and incentives for reviewers are proposed as essential to ensure a balanced academic environment., Summary: AI's incorporation in scientific publishing is promising yet comes with significant ethical and operational challenges. The role of human reviewers is accentuated, ensuring authenticity in an AI-influenced environment., Outlook: As the scientific community treads the path of AI integration, a balanced symbiosis between AI's efficiency and human discernment is pivotal. Emphasizing human expertise, while exploit artificial intelligence responsibly, will determine the trajectory of an ethically sound and efficient AI-augmented future in scientific publishing., (© 2023 Walter de Gruyter GmbH, Berlin/Boston.)
- Published
- 2023
- Full Text
- View/download PDF
13. Faculty Members' Use of Artificial Intelligence to Grade Student Papers: A Case of Implications
- Author
-
Kumar, Rahul
- Abstract
This paper presents the case of an adjunct university professor to illustrate the dilemma of using artificial intelligence (AI) technology to grade student papers. The hypothetical case discusses the benefits of using a commercial AI service to grade student papers--including discretion, convenience, pedagogical merits of consistent feedback for students, and advances made in the field that yield high-quality work--all of which are achieved quickly. Arguments against using AI to grade student papers involve cost, privacy, legality, and ethics. The paper discusses career implications for faculty members in both situations and concludes with implications for researchers within the discourse on academic integrity.
- Published
- 2023
- Full Text
- View/download PDF
14. Detection of fake papers in the era of artificial intelligence.
- Author
-
Dadkhah M, Oermann MH, Hegedüs M, Raman R, and Dávid LD
- Subjects
- Humans, Artificial Intelligence, Peer Review
- Abstract
Objectives: Paper mills, companies that write scientific papers and gain acceptance for them, then sell authorships of these papers, present a key challenge in medicine and other healthcare fields. This challenge is becoming more acute with artificial intelligence (AI), where AI writes the manuscripts and then the paper mills sell the authorships of these papers. The aim of the current research is to provide a method for detecting fake papers., Methods: The method reported in this article uses a machine learning approach to create decision trees to identify fake papers. The data were collected from Web of Science and multiple journals in various fields., Results: The article presents a method to identify fake papers based on the results of decision trees. Use of this method in a case study indicated its effectiveness in identifying a fake paper., Conclusions: This method to identify fake papers is applicable for authors, editors, and publishers across fields to investigate a single paper or to conduct an analysis of a group of manuscripts. Clinicians and others can use this method to evaluate articles they find in a search to ensure they are not fake articles and instead report actual research that was peer reviewed prior to publication in a journal., (© 2023 Walter de Gruyter GmbH, Berlin/Boston.)
- Published
- 2023
- Full Text
- View/download PDF
15. Reply to "Artificial intelligence in writing of papers: some considerations".
- Author
-
Vintzileos AM, Chavez MR, and Romero R
- Subjects
- Humans, Artificial Intelligence, Writing
- Published
- 2023
- Full Text
- View/download PDF
16. AI beats human sleuth at finding problematic images in research papers.
- Author
-
Oza A
- Subjects
- Humans, Artificial Intelligence standards, Pattern Recognition, Automated standards, Research Report standards, Photography standards
- Published
- 2023
- Full Text
- View/download PDF
17. Assessing the performance of ChatGPT to solve biochemistry question papers of university examination.
- Author
-
Mahat RK, Jantikar AM, Rathore V, and Panda S
- Subjects
- Humans, Universities, Artificial Intelligence, Biochemistry education, Academic Performance
- Published
- 2023
- Full Text
- View/download PDF
18. Artificial intelligence and "the Art of Kintsugi" in Anesthesiology: ten influential papers for clinical users.
- Author
-
Bellini V, Russo M, Lanza R, Domenichetti T, Compagnone C, Maggiore SM, Cammarota G, Pelosi P, Vetrugno L, and Bignami EG
- Subjects
- Humans, Artificial Intelligence, Anesthesiology
- Abstract
Artificial intelligence refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. In the present review we chose ten influential papers from the last five years and through Kintsugi, shed the light on recent evolution of artificial intelligence in anesthesiology. A comprehensive search in in Medline, Embase, Web of Science and Scopus databases was conducted. Each author searched the databases independently and created a list of six articles that influenced their clinical practice during this period, with a focus on their area of competence. During a subsequent step, each researcher presented his own list and most cited papers were selected to create the final collection of ten articles. In recent years purely methodological works with a cryptic technology (black-box) represented by the intact and static vessel, translated to a "modern artificial intelligence" in clinical practice and comprehensibility (glass-box). The purposes of this review are to explore the ten most cited papers about artificial intelligence in anesthesiology and to understand how and when it should be integrated in clinical practice.
- Published
- 2023
- Full Text
- View/download PDF
19. Artificial intelligence and machine learning for disaster prediction: a scientometric analysis of highly cited papers
- Author
-
Kappi, Mallikarjun and Mallikarjuna, B.
- Published
- 2024
- Full Text
- View/download PDF
20. mLearning versus Paper and Pencil Practice for Telling Time: Impact for Attention and Accuracy
- Author
-
DiCarlo, Cynthia F., Deris, Aaron R., and Deris, Thomas P.
- Abstract
The purpose of this study was to investigate the impact of mLearning or mobile device practice on the attention and accuracy of student's use of math concepts, specifically, telling time. A single subject, alternating treatment design was used to compare mLearning to paper and pencil practice in four 3rd grade male students. Results were mixed; two children were observed to be more on-task during the mLearning practice, and two children were observed to perform similarly across both conditions. Additionally, two children performed similarly on correctly completed problems across both conditions, and two children performed better using paper and pencil practice. All students completed more math problems during the paper and pencil practice.
- Published
- 2023
- Full Text
- View/download PDF
21. Distinguishing ChatGPT(-3.5, -4)-generated and human-written papers through Japanese stylometric analysis.
- Author
-
Zaitsu W and Jin M
- Subjects
- Humans, Random Forest, Artificial Intelligence, Writing
- Abstract
In the first half of 2023, text-generative artificial intelligence (AI), including ChatGPT from OpenAI, has attracted considerable attention worldwide. In this study, first, we compared Japanese stylometric features of texts generated by ChatGPT, equipped with GPT-3.5 and GPT-4, and those written by humans. In this work, we performed multi-dimensional scaling (MDS) to confirm the distributions of 216 texts of three classes (72 academic papers written by 36 single authors, 72 texts generated by GPT-3.5, and 72 texts generated by GPT-4 on the basis of the titles of the aforementioned papers) focusing on the following stylometric features: (1) bigrams of parts-of-speech, (2) bigram of postpositional particle words, (3) positioning of commas, and (4) rate of function words. MDS revealed distinct distributions at each stylometric feature of GPT (3.5 and 4) and human. Although GPT-4 is more powerful than GPT-3.5 because it has more parameters, both GPT (3.5 and 4) distributions are overlapping. These results indicate that although the number of parameters may increase in the future, GPT-generated texts may not be close to that written by humans in terms of stylometric features. Second, we verified the classification performance of random forest (RF) classifier for two classes (GPT and human) focusing on Japanese stylometric features. This study revealed the high performance of RF in each stylometric feature: The RF classifier focusing on the rate of function words achieved 98.1% accuracy. Furthermore the RF classifier focusing on all stylometric features reached 100% in terms of all performance indexes (accuracy, recall, precision, and F1 score). This study concluded that at this stage we human discriminate ChatGPT from human limited to Japanese language., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Zaitsu, Jin. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
- Published
- 2023
- Full Text
- View/download PDF
22. Use of Artificial Intelligence in Radiology: Impact on Pediatric Patients, a White Paper From the ACR Pediatric AI Workgroup.
- Author
-
Sammer MBK, Akbari YS, Barth RA, Blumer SL, Dillman JR, Farmakis SG, Frush DP, Gokli A, Halabi SS, Iyer R, Joshi A, Kwon JK, Otero HJ, Sher AC, Sotardi ST, Taragin BH, Towbin AJ, and Wald C
- Subjects
- Adult, Humans, Child, Societies, Medical, Radiography, Diagnostic Imaging methods, Artificial Intelligence, Radiology methods
- Abstract
In this white paper, the ACR Pediatric AI Workgroup of the Commission on Informatics educates the radiology community about the health equity issue of the lack of pediatric artificial intelligence (AI), improves the understanding of relevant pediatric AI issues, and offers solutions to address the inadequacies in pediatric AI development. In short, the design, training, validation, and safe implementation of AI in children require careful and specific approaches that can be distinct from those used for adults. On the eve of widespread use of AI in imaging practice, the group invites the radiology community to align and join Image IntelliGently (www.imageintelligently.org) to ensure that the use of AI is safe, reliable, and effective for children., (Copyright © 2023 American College of Radiology. Published by Elsevier Inc. All rights reserved.)
- Published
- 2023
- Full Text
- View/download PDF
23. Can an Artificial Intelligence (AI) Be an Author on a Medical Paper?
- Author
-
Portnoy JM and Oppenheimer JJ
- Subjects
- Artificial Intelligence, Authorship
- Published
- 2023
- Full Text
- View/download PDF
24. Explainable AI in radiology: a white paper of the Italian Society of Medical and Interventional Radiology.
- Author
-
Neri E, Aghakhanyan G, Zerunian M, Gandolfo N, Grassi R, Miele V, Giovagnoni A, and Laghi A
- Subjects
- Humans, Radiography, Radiologists, Algorithms, Radiology, Interventional, Artificial Intelligence
- Abstract
The term Explainable Artificial Intelligence (xAI) groups together the scientific body of knowledge developed while searching for methods to explain the inner logic behind the AI algorithm and the model inference based on knowledge-based interpretability. The xAI is now generally recognized as a core area of AI. A variety of xAI methods currently are available to researchers; nonetheless, the comprehensive classification of the xAI methods is still lacking. In addition, there is no consensus among the researchers with regards to what an explanation exactly is and which are salient properties that must be considered to make it understandable for every end-user. The SIRM introduces an xAI-white paper, which is intended to aid Radiologists, medical practitioners, and scientists in the understanding an emerging field of xAI, the black-box problem behind the success of the AI, the xAI methods to unveil the black-box into a glass-box, the role, and responsibilities of the Radiologists for appropriate use of the AI-technology. Due to the rapidly changing and evolution of AI, a definitive conclusion or solution is far away from being defined. However, one of our greatest responsibilities is to keep up with the change in a critical manner. In fact, ignoring and discrediting the advent of AI a priori will not curb its use but could result in its application without awareness. Therefore, learning and increasing our knowledge about this very important technological change will allow us to put AI at our service and at the service of the patients in a conscious way, pushing this paradigm shift as far as it will benefit us., (© 2023. The Author(s).)
- Published
- 2023
- Full Text
- View/download PDF
25. Artificial intelligence publications: synthetic data, patients, and papers.
- Author
-
Mavrogenis AF and Scarlat MM
- Subjects
- Humans, Artificial Intelligence, Patients
- Published
- 2023
- Full Text
- View/download PDF
26. Human, all too human - why artificial intelligence cannot "author" papers.
- Author
-
Abbasi K
- Subjects
- Humans, Artificial Intelligence, Writing
- Published
- 2023
- Full Text
- View/download PDF
27. Elements of a Good Radiology Artificial Intelligence Paper.
- Author
-
Gong B, Soyer P, McInnes MDF, and Patlas MN
- Subjects
- Humans, Radiography, Artificial Intelligence, Radiology
- Published
- 2023
- Full Text
- View/download PDF
28. Can We Write a Research Paper Using Artificial Intelligence?
- Author
-
Narayanaswamy CS
- Subjects
- Humans, Artificial Intelligence, Writing
- Published
- 2023
- Full Text
- View/download PDF
29. Artificial intelligence and the creation of scientific papers.
- Author
-
Sánchez-Sotelo J, Jed Kuhn JE, and Mallon WJ
- Subjects
- Humans, Publishing, Artificial Intelligence
- Published
- 2023
- Full Text
- View/download PDF
30. From data analysis to paper writing: How Artificial intelligence is changing the face of scientific literature.
- Author
-
Marchi F and Sampieri C
- Subjects
- Humans, Data Analysis, Artificial Intelligence, Writing
- Abstract
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
- Published
- 2023
- Full Text
- View/download PDF
31. [Fake paper factories: root cause solutions are needed.]
- Author
-
Caminiti C and De Fiore L
- Subjects
- Humans, Plagiarism, Peer Review, Software, Artificial Intelligence, Publishing
- Abstract
The pressure to publish academic papers for career advancement and technological innovations have fostered the growth of a new phenomenon, the serial fabrication of articles to be submitted to scientific journals. Papers with fake content are produced by specialised publishing agencies. Journal editors and publishers increased vigilance and control, tightening the peer review process and using anti-plagiarism software. But, being a systemic issue, it is not easy to find the solution and action must be taken on its causes: greater awareness of research ethics is needed, specific training for young doctors and - in the long run - an appropriate use of artificial intelligence, which should become a tool for protecting the integrity of knowledge.
- Published
- 2023
- Full Text
- View/download PDF
32. Making paper labels smart for augmented wine recognition
- Author
-
Angeli, Alessia, Stacchio, Lorenzo, Donatiello, Lorenzo, Giacchè, Alessandro, and Marfia, Gustavo
- Published
- 2024
- Full Text
- View/download PDF
33. How paediatric drug development and use could benefit from OMICs: A c4c expert group white paper.
- Author
-
Neumann E, Schreeck F, Herberg J, Jacqz Aigrain E, Maitland-van der Zee AH, Pérez-Martínez A, Hawcutt DB, Schaeffeler E, Rane A, de Wildt SN, and Schwab M
- Subjects
- Humans, Child, Biological Specimen Banks, Prospective Studies, Metabolomics methods, Biomarkers, Drug Development, Artificial Intelligence, Pediatrics
- Abstract
The safety and efficacy of pharmacotherapy in children, particularly preterms, neonates and infants, is limited by a paucity of good-quality data from prospective clinical drug trials. A specific challenge is the establishment of valid biomarkers. OMICs technologies may support these efforts by complementary information about targeted and nontargeted molecules through systematic characterization and quantitation of biological samples. OMICs technologies comprise at least genomics, epigenomics, transcriptomics, proteomics, metabolomics and microbiomics in addition to the patient's phenotype. OMICs technologies are in part hypothesis-generating, allowing an in depth understanding of disease pathophysiology and pharmacological mechanisms. Application of OMICs technologies in paediatrics faces major challenges before routine adoption. First, developmental processes need to be considered, including a subdivision into specific age groups as developmental changes clearly impact OMICs data. Second, compared to the adult population, the number of patients is limited as are the type and amount of necessary biomaterial, especially in neonates and preterms. Thus, advanced trial designs and biostatistical methods, noninvasive biomarkers, innovative biobanking concepts including data and samples from healthy children, as well as analytical approaches (eg liquid biopsies) should be addressed to overcome these obstacles. The ultimate goal is to link OMICs technologies with innovative analysis tools, such as artificial intelligence at an early stage. The use of OMICs data based on a feasible approach will contribute to the identification complex phenotypes and subpopulations of patients to improve the development of medicines for children with potential economic advantages., (© 2022 The Authors. British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)
- Published
- 2022
- Full Text
- View/download PDF
34. The Challenges of Regulating Artificial Intelligence in Healthcare Comment on "Clinical Decision Support and New Regulatory Frameworks for Medical Devices: Are We Ready for It? - A Viewpoint Paper".
- Author
-
McKee M and Wouters OJ
- Subjects
- Humans, Delivery of Health Care, Health Facilities, Technology, Artificial Intelligence, Decision Support Systems, Clinical
- Abstract
Regulation of health technologies must be rigorous, instilling trust among both healthcare providers and patients. This is especially important for the control and supervision of the growing use of artificial intelligence in healthcare. In this commentary on the accompanying piece by Van Laere and colleagues, we set out the scope for applying artificial intelligence in the healthcare sector and outline five key challenges that regulators face in dealing with these modern-day technologies. Addressing these challenges will not be easy. While artificial intelligence applications in healthcare have already made rapid progress and benefitted patients, these applications clearly hold even more potential for future developments. Yet it is vital that the regulatory environment keep up with this fast-evolving space of healthcare in order to anticipate and, to the extent possible, prevent the risks that may arise., (© 2023 The Author(s); Published by Kerman University of Medical Sciences This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.)
- Published
- 2023
- Full Text
- View/download PDF
35. ChatGPT listed as author on research papers: many scientists disapprove.
- Author
-
Stokel-Walker C
- Subjects
- Authorship, Publishing legislation & jurisprudence, Publishing trends, Artificial Intelligence legislation & jurisprudence, Artificial Intelligence trends, Research Report standards, Research Report trends
- Published
- 2023
- Full Text
- View/download PDF
36. Challenges in cybersecurity: A perspective paper presented at the 8th World Business Ethics Forum, Hang Seng University, Hong Kong (June 14, 2023)
- Author
-
Tang, Thomas S. K.
- Published
- 2024
- Full Text
- View/download PDF
37. Could AI help you to write your next paper?
- Author
-
Hutson M
- Subjects
- Research Personnel, Artificial Intelligence, Authorship, Writing, Research Report
- Published
- 2022
- Full Text
- View/download PDF
38. Using ChatGPT To Write Scientific Papers In Indonesia: A Systematic Review
- Author
-
Suntoro Suntoro, Ida Zulaeha, Hari Bakti Mardikantoro, and Tommi Yuniawan
- Subjects
ChatGPT ,writing scientific papers ,artificial intelligence ,systematic review ,Social Sciences - Abstract
Background: The utilization of ChatGPT in writing scientific papers has sparked both pros and cons in Indonesia. Some studies reveal its great potential, while others highlight the negative impacts resulting from the use of ChatGPT. Objective: This research aims to analyze the area, impact, and trends in the use of ChatGPT in writing scientific papers in Indonesia through a systematic review. Methodology: Researchers use PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) to conduct the analysis. The sample consists of 19 selected studies collected from the Google Scholar and Scopus databases. Data analysis uses quantitative and qualitative descriptive methods. Result: The research results show that the areas in which ChatGPT is used in writing scientific papers include topic selection, reference search, data analysis, scientific grammar, and translation. The use of ChatGPT in writing scientific papers faces some serious challenges, especially those related to ethics and academic integrity, such as increasing rates of plagiarism and declining values of honesty and responsibility. Moreover, dependence on artificial intelligence technology has the potential to reduce the development of human intellectual abilities, such as critical thinking, analysis, interpretation, and logic. Until recently, the research trend related to the use of ChatGPT for writing scientific papers is increasing, with the quite low density of research topics; thus, there are opportunities for further research to be carried out. Conclusion: The utilization of ChatGPT in academic writing in Indonesia has both positive and negative aspects. Regulation and morality can be crucial keys to realizing a quality academic environment. Unique Contribution: This research contributes to understanding the opportunities and challenges of utilizing ChatGPT in writing scientific papers, as well as providing information regarding areas that have the potential for further research. Key Recommendation: An in-depth understanding of the appropriate regulations for the use of ChatGPT in writing scientific papers is needed to minimize risks while still maximizing its positive potential.
- Published
- 2024
39. Pasteur’s quadrant in AI: do patent-cited papers have higher scientific impact?
- Author
-
Gao, Xingyu, Wu, Qiang, Liu, Yuanyuan, and Yang, Ruilu
- Published
- 2024
- Full Text
- View/download PDF
40. Automated assessment of pen and paper tests using computer vision
- Author
-
Jocovic, Vladimir, Marinkovic, Milan, Stojanovic, Sasa, and Nikolic, Bosko
- Published
- 2024
- Full Text
- View/download PDF
41. Defining digital surgery: a SAGES white paper
- Author
-
Ali, Jawad T., Yang, Gene, Green, Courtney A., Reed, Benjamin L., Madani, Amin, Ponsky, Todd A., Hazey, Jeffrey, Rothenberg, Steven S., Schlachta, Christopher M., Oleynikov, Dmitry, and Szoka, Nova
- Published
- 2024
- Full Text
- View/download PDF
42. One Hundred Most-cited Papers on Bacterial Meningitis: A Bibliometric Study.
- Author
-
Hakkaraki, Vinayak Parashuram
- Subjects
BACTERIAL meningitis ,SERIAL publications ,DATABASES ,MEDICAL information storage & retrieval systems ,ARTIFICIAL intelligence ,BRAIN ,CITATION analysis ,DESCRIPTIVE statistics ,PUBLISHING ,BIBLIOMETRICS ,DATA analysis software ,ELECTRONIC publications ,BACTERIAL diseases ,TIME - Abstract
Background: In previous decades, large-scale research has been carried out on bacterial meningitis. In every field, citation analysis is the most significant contribution. The study's objective was to identify and analyze the 100 articles on bacterial meningitis that received the most citations between 2000 and 2023, highlighting the most significant developments in the field. Objective: The objective of this study was to find out what makes a highly influential article by identifying and analyzing the characteristics of the 100 articles in the field of bacterial meningitis that receive the most citations. The goal of this study was to find and examine the 100 articles on bacterial meningitis that received the most citations. Methodology: We identified the top 100 most-cited papers in the field of bacterial meningitis from 55 journals using the Dimensions AI database. The results of each author's analysis of 100 articles were then compared. We gathered fundamental data such as the journal's title, country of publication, and study type. Descriptive counts or percentages were used to compare the various categories. Results: Between the year 2000 and the year 2023, articles were published. The total number of citations ranged from 115 to 1176, with 42 papers receiving more than 200 citations. In 2008, 14 articles were published, followed by 10 in 2000 and 2007. One thousand one hundred and seventy-six times were given to the most-cited paper, whereas 115 times were given to the least-cited article. "Clinical Features and Prognostic Factors in Adults with Bacterial Meningitis," by Diederik van de Beek, et al. (2004) was the article that received the most citations. 1176 people have cited this article. van de Beek Diederik of the Academic Medical Center in The Netherlands is the author who has written the most articles, was mentioned in 14 of the top 100 articles. Papers were primarily published in Pediatrics (n = 9) publication with 1861 citations. The Netherlands came in second with 18 publications, followed by the United States (n = 46). Conclusion: Our study uses bibliometrics and visualization analysis of the most important articles in this field to show the current state of research in the area of bacterial meningitis, provide a history of research trends, and offer a perspective for future bacterial predicts the growth of meningitis. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
43. Artificial Intelligence on Campus: Parameters for Thoughtful Action
- Author
-
Alec Thomson
- Abstract
Artificial intelligence tools have presented many challenges and opportunities to transform teaching and learning on college campuses. These changes are significant enough to require colleges to take action to create a framework by which faculty and students can navigate the proper usage of these tools. Rather than working to create entirely new policies strictly for addressing these new technologies, they should instead edit their existing academic integrity and intellectual property statements to incorporate explicit mentions of artificial intelligence.
- Published
- 2024
44. Investigating the impact of sewer overflow on the environment: A comprehensive literature review paper.
- Author
-
Owolabi TA, Mohandes SR, and Zayed T
- Subjects
- Humans, Sewage, Wastewater, Artificial Intelligence, Groundwater
- Abstract
Sewer networks play a pivotal role in our everyday lives by transporting the stormwater and urban sewage away from the urban areas. In this regard, Sewer Overflow (SO) has been considered as a detrimental threat to our environment and health, which results from the wastewater discharge into the environment. In order to grapple with such deleterious phenomenon, numerous studies have been conducted; however, there has not been any review paper that provides the researchers undertaking research in this area with the following inclusive picture: (1) detailed-scientometric analysis of the research undertaken hitherto, (2) the types of methodologies used in the previous studies, (3) the aspects of environment impacted by the SO occurrence, and (4) the gaps existing in the relative literature together with the potential future works to be undertaken. Based on the comprehensive review undertaken, it is observed that simulation and artificial intelligence-based methods have been the most popular approaches. In addition, it has come to the attention that the detrimental impacts associated with the SO are fourfold as follows: air, quality of water, soil, and business and structure. Among these, the majority of the studies' focus have been tilted towards the impact of SO on the quality of ground water. The outcomes of this state-of-the-art review provides the researchers and environmental engineers with inclusive hindsight in dealing with such serious issue, which in turn, this culminates in a significant improvement in our environment as well as humans' well-beings., (Copyright © 2021. Published by Elsevier Ltd.)
- Published
- 2022
- Full Text
- View/download PDF
45. ESUR/ESUI position paper: developing artificial intelligence for precision diagnosis of prostate cancer using magnetic resonance imaging.
- Author
-
Penzkofer T, Padhani AR, Turkbey B, Haider MA, Huisman H, Walz J, Salomon G, Schoots IG, Richenberg J, Villeirs G, Panebianco V, Rouviere O, Logager VB, and Barentsz J
- Subjects
- Humans, Image-Guided Biopsy, Magnetic Resonance Imaging, Male, Artificial Intelligence, Prostatic Neoplasms diagnostic imaging
- Abstract
Artificial intelligence developments are essential to the successful deployment of community-wide, MRI-driven prostate cancer diagnosis. AI systems should ensure that the main benefits of biopsy avoidance are delivered while maintaining consistent high specificities, at a range of disease prevalences. Since all current artificial intelligence / computer-aided detection systems for prostate cancer detection are experimental, multiple developmental efforts are still needed to bring the vision to fruition. Initial work needs to focus on developing systems as diagnostic supporting aids so their results can be integrated into the radiologists' workflow including gland and target outlining tasks for fusion biopsies. Developing AI systems as clinical decision-making tools will require greater efforts. The latter encompass larger multicentric, multivendor datasets where the different needs of patients stratified by diagnostic settings, disease prevalence, patient preference, and clinical setting are considered. AI-based, robust, standard operating procedures will increase the confidence of patients and payers, thus enabling the wider adoption of the MRI-directed approach for prostate cancer diagnosis. KEY POINTS: • AI systems need to ensure that the benefits of biopsy avoidance are delivered with consistent high specificities, at a range of disease prevalence. • Initial work has focused on developing systems as diagnostic supporting aids for outlining tasks, so they can be integrated into the radiologists' workflow to support MRI-directed biopsies. • Decision support tools require a larger body of work including multicentric, multivendor studies where the clinical needs, disease prevalence, patient preferences, and clinical setting are additionally defined., (© 2021. The Author(s).)
- Published
- 2021
- Full Text
- View/download PDF
46. 'Words are flowing out like endless rain into a paper cup': ChatGPTand law school assessments
- Author
-
Hargreaves, Stuart
- Published
- 2023
47. Growing Australia's creative industry: The Australian Broadband Advisory Council creative industry expert working group position paper
- Author
-
Maric, Kris, Pizzica, Vince, and Nalbandian, Zareh
- Published
- 2024
48. Use of Artificial Intelligence-Based Software as Medical Devices for Chest Radiography: A Position Paper from the Korean Society of Thoracic Radiology.
- Author
-
Hwang EJ, Goo JM, Yoon SH, Beck KS, Seo JB, Choi BW, Chung MJ, Park CM, Jin KN, and Lee SM
- Subjects
- Humans, Radiography, Radiography, Thoracic, Republic of Korea, Software, Artificial Intelligence, Radiology
- Abstract
Competing Interests: Eui Jin Hwang received research grants from Lunit Inc., Coreline Soft, and Monitor corporation, outside the present study.
- Published
- 2021
- Full Text
- View/download PDF
49. Transforming Academic Library Operations in Africa with Artificial Intelligence: Opportunities and Challenges: A Review Paper
- Author
-
Echedom, Anthonia U. and Okuonghae, Omorodion
- Abstract
This paper focuses on the opportunities and challenges associated with the use of artificial intelligence (AI) in academic library operations. In the quest to render fast, effective and efficient services, academic libraries have adopted different technologies in the past. Artificial intelligence technologies is the latest among the technologies currently being introduced in libraries. The technology which is considered an intelligent system, come in the form of robots and expert systems which have natural language processing, machine learning and pattern recognition capabilities. This paper examined the features of AI, the application of AI to library operations, examples of academic libraries with AI technologies in Sub-Saharan Africa, the need for AI in libraries and the challenges associated with the adoption of AI in libraries. The study concluded that AI holds a lot of prospects for the improvement of information services delivery in African academic libraries. Consequently, its adoption is a sinequanon to delivering robust library services in the Fourth Industrial Revolution (4IR).
- Published
- 2021
- Full Text
- View/download PDF
50. Cardiovascular RNA markers and artificial intelligence may improve COVID-19 outcome: a position paper from the EU-CardioRNA COST Action CA17129.
- Author
-
Badimon L, Robinson EL, Jusic A, Carpusca I, deWindt LJ, Emanueli C, Ferdinandy P, Gu W, Gyöngyösi M, Hackl M, Karaduzovic-Hadziabdic K, Lustrek M, Martelli F, Nham E, Potočnjak I, Satagopam V, Schneider R, Thum T, and Devaux Y
- Subjects
- Cardiovascular Diseases diagnosis, Cardiovascular Diseases genetics, Cardiovascular System virology, Humans, Quality of Life, SARS-CoV-2 pathogenicity, Artificial Intelligence economics, Biomarkers analysis, COVID-19 diagnosis, RNA genetics
- Abstract
The coronavirus disease 2019 (COVID-19) pandemic has been as unprecedented as unexpected, affecting more than 105 million people worldwide as of 8 February 2020 and causing more than 2.3 million deaths according to the World Health Organization (WHO). Not only affecting the lungs but also provoking acute respiratory distress, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is able to infect multiple cell types including cardiac and vascular cells. Hence a significant proportion of infected patients develop cardiac events, such as arrhythmias and heart failure. Patients with cardiovascular comorbidities are at highest risk of cardiac death. To face the pandemic and limit its burden, health authorities have launched several fast-track calls for research projects aiming to develop rapid strategies to combat the disease, as well as longer-term projects to prepare for the future. Biomarkers have the possibility to aid in clinical decision-making and tailoring healthcare in order to improve patient quality of life. The biomarker potential of circulating RNAs has been recognized in several disease conditions, including cardiovascular disease. RNA biomarkers may be useful in the current COVID-19 situation. The discovery, validation, and marketing of novel biomarkers, including RNA biomarkers, require multi-centre studies by large and interdisciplinary collaborative networks, involving both the academia and the industry. Here, members of the EU-CardioRNA COST Action CA17129 summarize the current knowledge about the strain that COVID-19 places on the cardiovascular system and discuss how RNA biomarkers can aid to limit this burden. They present the benefits and challenges of the discovery of novel RNA biomarkers, the need for networking efforts, and the added value of artificial intelligence to achieve reliable advances., (© The Author(s) 2021. Published by Oxford University Press on behalf of the European Society of Cardiology.)
- Published
- 2021
- Full Text
- View/download PDF
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.