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Chat Generative Pre-trained Transformer (ChatGPT) is an artificial intelligence (AI) tool which utilises machine learning to generate original text resembling human language. AI models have recently demonstrated remarkable ability at analysing and solving problems, including passing professional examinations. We investigate the performance of ChatGPT on some of the UK radiology fellowship equivalent examination questions. ChatGPT was asked to answer questions from question banks resembling the Fellowship of the Royal College of Radiologists (FRCR) examination. The entire physics part 1 question bank (203 5-part true/false questions) was answered by the GPT-4 model and answers recorded. 240 single best answer questions (SBAs) (representing the true length of the FRCR 2A examination) were answered by both GPT-3.5 and GPT-4 models. ChatGPT 4 answered 74.8% of part 1 true/false statements correctly. The spring 2023 passing mark of the part 1 examination was 75.5% and ChatGPT thus narrowly failed. In the 2A examination, ChatGPT 3.5 answered 50.8% SBAs correctly, while GPT-4 answered 74.2% correctly. The winter 2022 2A pass mark was 63.3% and thus GPT-4 clearly passed. AI models such as ChatGPT are able to answer the majority of questions in an FRCR style examination. It is reasonable to assume that further developments in AI will be more likely to succeed in comprehending and solving questions related to medicine, specifically clinical radiology. Our findings outline the unprecedented capabilities of AI, adding to the current relatively small body of literature on the subject, which in turn can play a role medical training, evaluation and practice. This can undoubtedly have implications for radiology. [ABSTRACT FROM AUTHOR]

AI technology has made significant advancements in recent years, with the notable development of ChatGPT in November 2022. Users have observed evidence of deductive reasoning, logical thinking, and coherent thought in ChatGPT's responses. This study aimed to determine if ChatGPT has the capability to pass the Orthopaedic Fellow of the Royal College of Surgeons (FRCS Orth) Part A exam. To assess ChatGPT4's ability to pass the Orthopaedic FRCS Orth Part A exam, a study was conducted using 240 mock FRCS Orth Part A questions. The study evaluated the accuracy of ChatGPT's answers and the response time for each question. Descriptive statistics were employed to analyse the chatbot's performance. The evaluation revealed that ChatGPT4 achieved an overall score of 67.5% on Part A of the exam. However, ChatGPT4 did not meet the overall pass mark required for the FRCS Orth Part A exam. This study demonstrates that ChatGPT was unable to pass the FRCS Orthopaedic examination. Several factors contributed to this outcome, including the lack of critical or high-order thinking abilities, limited clinical expertise, and the inability to meet the rigorous requirements of the exam. • AI technology has made significant advancements in recent years • ChatGPT4 achieved an overall score of 67.5% on Part A of the exam • Chat GPT lacks critical or high-order thinking abilities and clinical expertise [ABSTRACT FROM AUTHOR]

Peer review is the established method for evaluating the quality and validity of research manuscripts in scholarly publishing. However, scientific peer review faces challenges as the volume of submitted research has steadily increased in recent years. Time constraints and peer review quality assurance can place burdens on reviewers, potentially discouraging their participation. Some artificial intelligence (AI) tools might assist in relieving these pressures. This study explores the efficiency and effectiveness of one of the artificial intelligence (AI) chatbots, ChatGPT (Generative Pre-trained Transformer), in the peer review process. Twenty-one peer-reviewed research articles were anonymised to ensure unbiased evaluation. Each article was reviewed by two humans and by versions 3.5 and 4.0 of ChatGPT. The AI was instructed to provide three positive and three negative comments on the articles and recommend whether they should be accepted or rejected. The human and AI results were compared using a 5-point Likert scale to determine the level of agreement. The correlation between ChatGPT responses and the acceptance or rejection of the papers was also examined. Subjective review similarity between human reviewers and ChatGPT showed a mean score of 3.6/5 for ChatGPT 3.5 and 3.76/5 for ChatGPT 4.0. The correlation between human and AI review scores was statistically significant for ChatGPT 3.5, but not for ChatGPT 4.0. ChatGPT can complement human scientific peer review, enhancing efficiency and promptness in the editorial process. However, a fully automated AI review process is currently not advisable, and ChatGPT's role should be regarded as highly constrained for the present and near future. [ABSTRACT FROM AUTHOR]

The exact prompts provided to ChatGPT in order to generate each of the articles are mentioned in Table 1 of our article under "Question" [[1]]. Effective governance, monitoring and establishing stringent guidelines and frameworks, is paramount to ensure that the capabilities of AI language tools are appropriately leveraged in academic research, and also to explore the ethical and legal implications and potential biases. AI language models nonetheless have the potential to serve as a valuable adjunctive tool in research, and collaborative publishing by humans with the help of AI tools may drive academic writing in the future [[3]]. [Extracted from the article]

Whilst ChatGPT and possibly other AI-based technologies may find useful applications in Rheumatology and other medical specialities, concerns about the adoption of ChatGPT in the clinical context are understandable. Chat Generative Pre-Trained Transformer (ChatGPT), an artificial intelligence (AI) tool developed by Open AI based on Natural Language Processing models (NLP) has the ability to respond to human prompts following the acquisition of data, information analysis and application of Machine Learning (ML) algorithms. Considering its capabilities, ChatGPT has the potential to assist in rheumatology care delivery, specifically in the following areas: Patient disease modifying drug education: Drug education is critical in managing autoimmune disease patients. [Extracted from the article]