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51. A Systematic Meta-Analysis of Blockchain Technology for Educational Sector and Its Advancements towards Education 4.0

Author

Haque, Mustafizul, Kumar, V. Vijaya, Singh, Preeti, Goyal, Adheer A., Upreti, Kamal, and Verma, Ankit

Abstract

Now a days with the rapidly increasing development of technology and communication system, the implementation of blockchain is continuously increasing in various sectors. With the increase in massive data in educational sectors there arise a requirement of handling such enormous data. This can be easily and securely handled by blockchain technology due to its scalability, robustness, and resilience characteristics. In this paper, a methodology is presented for systematic meta-analysis of the blockchain applications, technologies, and integration of next-gen technologies for the deployment of education 4.0. The bibliometric analysis, the methodology is divided into three steps: selection strategy, inclusion strategy, and meta-analysis of research contributions are provided based on PRISMA-P. In the selection strategy, different research sources are searched. Selection and sorting of contributing research articles are performed in the inclusion strategy and finally, in a meta-analysis, the critical assessment of the educational management system and security aspects with blockchain deployment is performed. It was observed that most of the research contributions are theoretical concept based without any practical validations. From the results, it was also observed that the blockchain designs presented mainly focus on confidentiality, integrity, and availability. But apart from these, other security concerns such as scalability, flexibility, authorization, mutual authentication, attack resistant, etc. are not explored most. Further, the paper presented a critical analysis of next-gen technologies with blockchain for future education 4.0. This paper is focused to analyze the growing demand of the educational blockchain paradigm (EBP). For this paper presented a meta-analysis of existing research contributions concerning the application area, technology used, real-world examples, and next-gen technologies in education 4.0. Therefore, this paper will enlighten the focus of researchers for future research innovations.

Published
2023
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53. Medicinal Aspects of Saccharum munja

Author

Rahar, Sandeep, Nagpal, Navneet, Swami, Gaurav, Arora, Manisha, Bansal, Suraj, Goyal, Sandeep, Singla, Shwali, Singh, Preeti, and Kapoor, Reni

Published
2010

58. Identification and Classification of Depressed Patients Using Machine Learning – A Review

Author

Kumar, Ajay, Banerjee, Kakoli, Kumar, Pradeep, Tyagi, Priyanshi, Singh, Preeti, Thapar, Prisha, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Garg, Lalit, editor, Kesswani, Nishtha, editor, Brigui, Imene, editor, Dewangan, Bhupesh Kr., editor, Shukla, R. N., editor, and Sisodia, Dilip Singh, editor

Published
2024
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59. The Type 2 Diabetes Knowledge Portal: An open access genetic resource dedicated to type 2 diabetes and related traits

Author

Costanzo, Maria C, von Grotthuss, Marcin, Massung, Jeffrey, Jang, Dongkeun, Caulkins, Lizz, Koesterer, Ryan, Gilbert, Clint, Welch, Ryan P, Kudtarkar, Parul, Hoang, Quy, Boughton, Andrew P, Singh, Preeti, Sun, Ying, Duby, Marc, Moriondo, Annie, Nguyen, Trang, Smadbeck, Patrick, Alexander, Benjamin R, Brandes, MacKenzie, Carmichael, Mary, Dornbos, Peter, Green, Todd, Huellas-Bruskiewicz, Kenneth C, Ji, Yue, Kluge, Alexandria, McMahon, Aoife C, Mercader, Josep M, Ruebenacker, Oliver, Sengupta, Sebanti, Spalding, Dylan, Taliun, Daniel, Consortium, AMP-T2D, Abecasis, Gonçalo, Akolkar, Beena, Allred, Nicholette D, Altshuler, David, Below, Jennifer E, Bergman, Richard, Beulens, Joline WJ, Blangero, John, Boehnke, Michael, Bokvist, Krister, Bottinger, Erwin, Bowden, Donald, Brosnan, M Julia, Brown, Christopher, Bruskiewicz, Kenneth, Burtt, Noël P, Cebola, Inês, Chambers, John, Chen, Yii-Der Ida, Cherkas, Andriy, Chu, Audrey Y, Clark, Christopher, Claussnitzer, Melina, Cox, Nancy J, Hoed, Marcel den, Dong, Duc, Duggirala, Ravindranath, Dupuis, Josée, Elders, Petra JM, Engreitz, Jesse M, Fauman, Eric, Ferrer, Jorge, Flannick, Jason, Flicek, Paul, Flickinger, Matthew, Florez, Jose C, Fox, Caroline S, Frayling, Timothy M, Frazer, Kelly A, Gaulton, Kyle J, Gloyn, Anna L, Hanis, Craig L, Hanson, Robert, Hattersley, Andrew T, Im, Hae Kyung, Iqbal, Sidra, Jacobs, Suzanne BR, Jang, Dong-Keun, Jordan, Tad, Kamphaus, Tania, Karpe, Fredrik, Keane, Thomas M, Kim, Seung K, Lage, Kasper, Lange, Leslie A, and Lazar, Mitchell

Subjects
Genetics, Diabetes, Human Genome, Metabolic and endocrine, Good Health and Well Being, Humans, Diabetes Mellitus, Type 2, Access to Information, Prospective Studies, Genomics, Phenotype, AMP-T2D Consortium, CMDKP, GWAS, T2DKP, data sharing, diabetes, effector genes, genetic associations, genetic support, genomics, portal, Biochemistry and Cell Biology, Medical Biochemistry and Metabolomics, Endocrinology & Metabolism
Abstract

Associations between human genetic variation and clinical phenotypes have become a foundation of biomedical research. Most repositories of these data seek to be disease-agnostic and therefore lack disease-focused views. The Type 2 Diabetes Knowledge Portal (T2DKP) is a public resource of genetic datasets and genomic annotations dedicated to type 2 diabetes (T2D) and related traits. Here, we seek to make the T2DKP more accessible to prospective users and more useful to existing users. First, we evaluate the T2DKP's comprehensiveness by comparing its datasets with those of other repositories. Second, we describe how researchers unfamiliar with human genetic data can begin using and correctly interpreting them via the T2DKP. Third, we describe how existing users can extend their current workflows to use the full suite of tools offered by the T2DKP. We finally discuss the lessons offered by the T2DKP toward the goal of democratizing access to complex disease genetic results.

Published
2023

64. Discovering novel systemic biomarkers in photos of the external eye

Author

Babenko, Boris, Traynis, Ilana, Chen, Christina, Singh, Preeti, Uddin, Akib, Cuadros, Jorge, Daskivich, Lauren P., Maa, April Y., Kim, Ramasamy, Kang, Eugene Yu-Chuan, Matias, Yossi, Corrado, Greg S., Peng, Lily, Webster, Dale R., Semturs, Christopher, Krause, Jonathan, Varadarajan, Avinash V., Hammel, Naama, and Liu, Yun

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Quantitative Biology - Quantitative Methods
Abstract

External eye photos were recently shown to reveal signs of diabetic retinal disease and elevated HbA1c. In this paper, we evaluate if external eye photos contain information about additional systemic medical conditions. We developed a deep learning system (DLS) that takes external eye photos as input and predicts multiple systemic parameters, such as those related to the liver (albumin, AST); kidney (eGFR estimated using the race-free 2021 CKD-EPI creatinine equation, the urine ACR); bone & mineral (calcium); thyroid (TSH); and blood count (Hgb, WBC, platelets). Development leveraged 151,237 images from 49,015 patients with diabetes undergoing diabetic eye screening in 11 sites across Los Angeles county, CA. Evaluation focused on 9 pre-specified systemic parameters and leveraged 3 validation sets (A, B, C) spanning 28,869 patients with and without diabetes undergoing eye screening in 3 independent sites in Los Angeles County, CA, and the greater Atlanta area, GA. We compared against baseline models incorporating available clinicodemographic variables (e.g. age, sex, race/ethnicity, years with diabetes). Relative to the baseline, the DLS achieved statistically significant superior performance at detecting AST>36, calcium<8.6, eGFR<60, Hgb<11, platelets<150, ACR>=300, and WBC<4 on validation set A (a patient population similar to the development sets), where the AUC of DLS exceeded that of the baseline by 5.2-19.4%. On validation sets B and C, with substantial patient population differences compared to the development sets, the DLS outperformed the baseline for ACR>=300 and Hgb<11 by 7.3-13.2%. Our findings provide further evidence that external eye photos contain important biomarkers of systemic health spanning multiple organ systems. Further work is needed to investigate whether and how these biomarkers can be translated into clinical impact.

Published
2022

70. Evaluating human genetic support for hypothesized metabolic disease genes

Author

Dornbos, Peter, Singh, Preeti, Jang, Dong-Keun, Mahajan, Anubha, Biddinger, Sudha B, Rotter, Jerome I, McCarthy, Mark I, and Flannick, Jason

Subjects
Biological Sciences, Genetics, Human Genome, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Human Genetics, Humans, Metabolic Diseases, Biochemistry and Cell Biology, Medical Biochemistry and Metabolomics, Endocrinology & Metabolism, Biochemistry and cell biology, Medical biochemistry and metabolomics
Abstract

We investigate the extent to which human genetic data are incorporated into studies that hypothesize novel links between genes and metabolic disease. To lower the barriers to using genetic data, we present an approach to enable researchers to evaluate human genetic support for experimentally determined hypotheses.

Published
2022

72. Differences Between Patient and Clinician-Taken Images: Implications for Virtual Care of Skin Conditions

Author

Rikhye, Rajeev V., Hong, Grace Eunhae, Singh, Preeti, Smith, Margaret Ann, Loh, Aaron, Muralidharan, Vijaytha, Wong, Doris, Sayres, Rory, Phung, Michelle, Betancourt, Nicolas, Fong, Bradley, Sahasrabudhe, Rachna, Nasim, Khoban, Eschholz, Alec, Matias, Yossi, Corrado, Greg S., Chou, Katherine, Webster, Dale R., Bui, Peggy, Liu, Yuan, Liu, Yun, Ko, Justin, and Lin, Steven

Published
2024
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75. Present Wind Energy Market Scenario in India

Author

Gupta, Sandeep, Singh, Preeti, Swami, Raju Kumar, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Namrata, Kumari, editor, Priyadarshi, Neeraj, editor, Bansal, Ramesh C., editor, and Kumar, Jitendra, editor

Published
2023
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76. Autocorrelation of an Econometric Model

Author

Singh, Preeti, Singh, Sarvpal, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Zhang, Yu-Dong, editor, Senjyu, Tomonobu, editor, So-In, Chakchai, editor, and Joshi, Amit, editor

Published
2023
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80. Detecting hidden signs of diabetes in external eye photographs

Author

Babenko, Boris, Mitani, Akinori, Traynis, Ilana, Kitade, Naho, Singh, Preeti, Maa, April, Cuadros, Jorge, Corrado, Greg S., Peng, Lily, Webster, Dale R., Varadarajan, Avinash, Hammel, Naama, and Liu, Yun

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Diabetes-related retinal conditions can be detected by examining the posterior of the eye. By contrast, examining the anterior of the eye can reveal conditions affecting the front of the eye, such as changes to the eyelids, cornea, or crystalline lens. In this work, we studied whether external photographs of the front of the eye can reveal insights into both diabetic retinal diseases and blood glucose control. We developed a deep learning system (DLS) using external eye photographs of 145,832 patients with diabetes from 301 diabetic retinopathy (DR) screening sites in one US state, and evaluated the DLS on three validation sets containing images from 198 sites in 18 other US states. In validation set A (n=27,415 patients, all undilated), the DLS detected poor blood glucose control (HbA1c > 9%) with an area under receiver operating characteristic curve (AUC) of 70.2; moderate-or-worse DR with an AUC of 75.3; diabetic macular edema with an AUC of 78.0; and vision-threatening DR with an AUC of 79.4. For all 4 prediction tasks, the DLS's AUC was higher (p<0.001) than using available self-reported baseline characteristics (age, sex, race/ethnicity, years with diabetes). In terms of positive predictive value, the predicted top 5% of patients had a 67% chance of having HbA1c > 9%, and a 20% chance of having vision threatening diabetic retinopathy. The results generalized to dilated pupils (validation set B, 5,058 patients) and to a different screening service (validation set C, 10,402 patients). Our results indicate that external eye photographs contain information useful for healthcare providers managing patients with diabetes, and may help prioritize patients for in-person screening. Further work is needed to validate these findings on different devices and patient populations (those without diabetes) to evaluate its utility for remote diagnosis and management.

Published
2020
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83. Pemphigoid Gestationis-A Rare Pregnancy Dermatoses.

Author

Dixit, Niharika and Singh, Preeti

Abstract

Pemphigoid gestationis is a rare subepidermal bullous dermatosis of pregnancy, caused by the interaction of IgG1 auto-antibodies with 180 kD BP Antigen 2. This disease can lead to preterm delivery, but the neonate is affected in only 10% cases. The treatment of choice in pemphigoid gestationis is systemic corticosteroids.

Published
2020

86. Lineage switching of the cellular distribution of BRAFV600E in multisystem Langerhans cell histiocytosis

Author

Milne, Paul, Bomken, Simon, Slater, Olga, Kumar, Ashish, Nelson, Adam, Roy, Somak, Velazquez, Jessica, Mankad, Kshitij, Nicholson, James, Yeomanson, Dan, Grundy, Richard, Kamal, Ahmed, Penn, Anthony, Pears, Jane, Millen, Gerard, Morland, Bruce, Hayden, James, Lam, Jason, Madkhali, Maymoon, MacDonald, Jamie, Singh, Preeti, Pagan, Sarah, Rodriguez-Galindo, Carlos, Minkov, Milen, Donadieu, Jean, Picarsic, Jennifer, Allen, Carl, Bigley, Venetia, and Collin, Matthew

Published
2023
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89. The Type 2 Diabetes Knowledge Portal: An open access genetic resource dedicated to type 2 diabetes and related traits

Author

Abecasis, Gonçalo, Akolkar, Beena, Alexander, Benjamin R., Allred, Nicholette D., Altshuler, David, Below, Jennifer E., Bergman, Richard, Beulens, Joline W.J., Blangero, John, Boehnke, Michael, Bokvist, Krister, Bottinger, Erwin, Boughton, Andrew P., Bowden, Donald, Brosnan, M. Julia, Brown, Christopher, Bruskiewicz, Kenneth, Burtt, Noël P., Carmichael, Mary, Caulkins, Lizz, Cebola, Inês, Chambers, John, Ida Chen, Yii-Der, Cherkas, Andriy, Chu, Audrey Y., Clark, Christopher, Claussnitzer, Melina, Costanzo, Maria C., Cox, Nancy J., Hoed, Marcel den, Dong, Duc, Duby, Marc, Duggirala, Ravindranath, Dupuis, Josée, Elders, Petra J.M., Engreitz, Jesse M., Fauman, Eric, Ferrer, Jorge, Flannick, Jason, Flicek, Paul, Flickinger, Matthew, Florez, Jose C., Fox, Caroline S., Frayling, Timothy M., Frazer, Kelly A., Gaulton, Kyle J., Gilbert, Clint, Gloyn, Anna L., Green, Todd, Hanis, Craig L., Hanson, Robert, Hattersley, Andrew T., Hoang, Quy, Im, Hae Kyung, Iqbal, Sidra, Jacobs, Suzanne B.R., Jang, Dong-Keun, Jordan, Tad, Kamphaus, Tania, Karpe, Fredrik, Keane, Thomas M., Kim, Seung K., Kluge, Alexandria, Koesterer, Ryan, Kudtarkar, Parul, Lage, Kasper, Lange, Leslie A., Lazar, Mitchell, Lehman, Donna, Liu, Ching-Ti, Loos, Ruth J.F., Ma, Ronald Ching-wan, MacDonald, Patrick, Massung, Jeffrey, Maurano, Matthew T., McCarthy, Mark I., McVean, Gil, Meigs, James B., Mercader, Josep M., Miller, Melissa R., Mitchell, Braxton, Mohlke, Karen L., Morabito, Samuel, Morgan, Claire, Mullican, Shannon, Narendra, Sharvari, Ng, Maggie C.Y., Nguyen, Lynette, Palmer, Colin N.A., Parker, Stephen C.J., Parrado, Antonio, Parsa, Afshin, Pawlyk, Aaron C., Pearson, Ewan R., Plump, Andrew, Province, Michael, Quertermous, Thomas, Redline, Susan, Reilly, Dermot F., Ren, Bing, Rich, Stephen S., Richards, J. Brent, Rotter, Jerome I., Ruebenacker, Oliver, Ruetten, Hartmut, Salem, Rany M., Sander, Maike, Sanders, Michael, Sanghera, Dharambir, Scott, Laura J., Sengupta, Sebanti, Siedzik, David, Sim, Xueling, Singh, Preeti, Sladek, Robert, Small, Kerrin, Smith, Philip, Stein, Peter, Spalding, Dylan, Stringham, Heather M., Sun, Ying, Susztak, Katalin, ’t Hart, Leen M., Taliun, Daniel, Taylor, Kent, Thomas, Melissa K., Todd, Jennifer A., Udler, Miriam S., Voight, Benjamin, von Grotthuss, Marcin, Wan, Andre, Welch, Ryan P., Wholley, David, Yuksel, Kaan, Zaghloul, Norann A., Jang, Dongkeun, Moriondo, Annie, Nguyen, Trang, Smadbeck, Patrick, Brandes, MacKenzie, Dornbos, Peter, Huellas-Bruskiewicz, Kenneth C., Ji, Yue, McMahon, Aoife C., Fauman, Eric B., Kamphaus, Tania Nayak, and Abecasis, Gonçalo R.

Published
2023
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92. Diagnosis, Treatment and Prevention of Nutritional Anemia in Children: Recommendations of the Joint Committee of Pediatric Hematology-Oncology Chapter and Pediatric and Adolescent Nutrition Society of the Indian Academy of Pediatrics

Author

Chandra, Jagdish, Dewan, Pooja, Kumar, Praveen, Mahajan, Amita, Singh, Preeti, Dhingra, Bhavna, Radhakrishnan, Nita, Sharma, Ratna, Manglani, Mamta, Rawat, Ashok Kumar, Gupta, Piyush, Gomber, Sunil, Bhat, Sunil, Gaikwad, Parag, Elizabeth, K. E., Bansal, Deepak, Dubey, Anand Prakash, Shah, Nitin, Kini, Pranoti, Trehan, Amita, Datta, Kalpana, Basavraja, G. V., Saxena, Vineet, and Kumar, Remesh R.

Published
2022
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