cirpublications.com-LoHG-1790878114-s068544189 1790878114 Clinical Intelligence Research Press info@cirpublications.com Clinical Intelligence Research Press Journal of Artificial Intelligence for Healthcare Systems J. Artif. Intell. Healthc. Syst. 3149-8981 2024 3 1 Fatima Zahra Amrani Youssef Benali Maria Gonzalez 2024 10.68159/s068544189 https://cirpublications.com/pub/journal/1/article/s068544189 Ghassemi M, Naumann T, Schulam P, Beam AL, Chen IY, Raghunathan A. Practical guidance on artificial intelligence for health-care data. Lancet Digit Health. 2019;1(4):e157-e169. 10.1016/S2589-7500(19)30023-6 Wiens J, Saria S, Sendak M, Ghassemi M, Liu VX, Doshi-Velez F, et al. Do no harm: a roadmap for responsible machine learning for health care. Nat Med. 2019;25(9):1337-40. 10.1038/s41591-019-0548-6 Rajpurkar P, Chen PJ, Banerjee O, Topol EJ. AI in health and medicine. Nat Med. 2022;28(1):31-8. 10.1038/s41591-021-01614-0 Sendak MP, Gao M, Brajer N, Balu S. Presenting machine learning model information to clinical end users with model facts labels. NPJ Digit Med. 2020;3:41. 10.1038/s41746-020-0253-3 Chen IY, Pierson E, Rose S, Joshi S, Ferryman K, Ghassemi M. Ethical machine learning in healthcare. J Am Med Inform Assoc. 2021;28(1):198-203. Lin H, Li R, Liu Z, Chen J, Yang Y, Chen H, et al. Diagnostic efficacy and therapeutic decision-making ability of an artificial intelligence-assisted electroencephalogram interpretation platform for childhood epilepsy: a multi-center randomized controlled trial. J Biomed Inform. 2023;129:104071. 10.1016/j.jbi.2023.104071 Yin J, Ng IAM, Xiong S, Wang J, Zhang J, Fan L, et al. MedSRGAN: medical images super-resolution using generative adversarial networks. Artif Intell Med. 2020;102:101770. 10.1016/j.artmed.2020.101770 Payne TH, Corley S, Cullen TA, Gandhi TK, Harrington L, Kuperman GJ, et al. Report of the AMIA EHR-2020 task force on the status and future direction of EHRs. J Am Med Inform Assoc. 2018;25(5):488-94. McKinney SM, Sieniek M, Godbole V, Godwin J, Antropova N, Ashrafian H, et al. International evaluation of an AI system for breast cancer screening. Nature. 2020;577(7788):89-94. 10.1038/s41586-019-1799-6 Beede E, Baylor E, Hersch F, Iurchenko A, Wilcox L, Ruamviboonsuk P, et al. A human-centered evaluation of a deep learning system deployed in clinics for the detection of diabetic retinopathy. Nat Med. 2020;26(5):654-6. 10.1038/s41591-020-0867-6 Tomašev N, Glorot X, Rae JW, Zielinski M, Askham H, Saraiva A, et al. A generalist AI-enabled clinical decision support system for healthcare. Nat Med. 2021;27(5):827-38. 10.1038/s41591-021-01337-0 Rudin C, Chen C, Wieland J, Madigan D, Dutta S, Perotte A. Interpretable machine learning for characterizing major depression and schizophrenia based on structural MRI. J Biomed Inform. 2021;124:103945. 10.1016/j.jbi.2021.103945 Gichoya JW, McCoy LG, Celi LA, Ghassemi M. AI recognition of patient race in medical imaging: a modelling study. Lancet Digit Health. 2022;4(6):e406-e414. 10.1016/S2589-7500(22)00063-2 Wahl B, Cossy-Gantner A, Germann S, Schwalbe NR. Artificial intelligence and global health: how can AI contribute to health in resource-poor settings? BMJ Glob Health. 2018;3(4):e000798. 10.1136/bmjgh-2018-000798 Gerke S, Minssen T, Cohen G. Ethical and legal challenges of artificial intelligence-driven healthcare. Artif Intell Med. 2020;102:101770. 10.1016/j.artmed.2019.101770 Lee CS, Nagy PG, Weaver SJ, Newman-Toker DE. Cognitive and system factors contributing to diagnostic errors in radiology. J Am Med Inform Assoc. 2018;25(6):745-52. Mhasawade V, Chunara R. Causal multi-level fairness. Patterns. 2021;2(1):100189. 10.1016/j.patter.2020.100189 Zhang K, Khosravi B, Vahdati S, Ghaffari A, Ghobadi A, Eslahi M, et al. A self-supervised deep learning model for anomaly detection in tabular data for label quality control in high-stakes clinical trials. Sci Data. 2023;10(1):20. 10.1038/s41597-022-01932-4 Yang Q, Steinfeld A, Rosé C, Zimmerman J. Re-examining whether, why, and how human-AI interaction is uniquely difficult to design. Digit Health. 2020;6:2055207620915905. 10.1177/2055207620915905 Chen M, Decary M. Artificial intelligence in healthcare: an essential guide for health leaders. Int J Med Inform. 2020;138:104129. 10.1016/j.ijmedinf.2020.104129 Reddy S, Allan S, Coghlan S, Cooper P. A governance model for the application of AI in health care. J Am Med Inform Assoc. 2020;27(3):491-7. Challen R, Denny J, Pitt M, Gompels L, Edwards T, Tsaneva-Atanasova K. Artificial intelligence, bias and clinical safety. BMJ Qual Saf. 2019;28(1):231-7. 10.1136/bmjqs-2018-008370 Xie Y, Seth I, Hunter-Smith DJ, Rozen WM, Ross R, Lee M. Aesthetic surgery advice and counseling from artificial intelligence: a rhinoplasty consultation with ChatGPT. Aesthetic Plast Surg. 2023;47(5):1985-93. 10.1007/s00266-023-03338-7 Jiang F, Jiang Y, Zhi H, Dong Y, Li H, Ma S, et al. Artificial intelligence in healthcare: past, present and future. IEEE J Biomed Health Inform. 2017;21(3):637-49. 10.1136/svn-2017-000101 Alami H, Lehoux P, Fleet R, Fortin JP, Liu J, Attieh R, et al. How can health systems better prepare for the next pandemic? PLOS Digit Health. 2022;1(5):e0000047. 10.1371/journal.pdig.0000047 Finlayson SG, Subbaswamy A, Singh K, Bowers J, Kupke A, McMurry J, et al. The clinician and dataset shift in artificial intelligence. Nat Commun. 2021;12(1):2067. 10.1056/NEJMp2101885 Seyyed-Kalantari L, Zhang H, McDermott MBA, Chen IY, Ghassemi M. Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations. Nat Med. 2021;27(12):2176-82. 10.1038/s41591-021-01595-0 Obermeyer Z, Powers B, Vogeli C, Mullainathan S. Dissecting racial bias in an algorithm used to manage the health of populations. Science. 2019;366(6464):447-53. 10.1126/science.aax2342 Adam NR, Wieder R, Ghosh D. Data science, learning, and applications to biomedical and health sciences. J Biomed Inform. 2017;66:1-6. 10.1111/nyas.13387 De Fauw J, Ledsam JR, Romera-Paredes B, Nikolov S, Tomasev N, Blackwell S, et al. Clinically applicable deep learning for diagnosis and referral in retinal disease. Nat Med. 2018;24(9):1342-50. 10.1038/s41591-018-0107-6 Rodriguez-Ruiz A, Lång K, Gubern-Merida A, Broeders M, Gennaro G, Clauser P, et al. Stand-alone artificial intelligence for breast cancer detection in mammography: comparison with radiologists. J Natl Cancer Inst. 2019;111(9):916-22. Vokinger KN, Feuerriegel S, Kesselheim AS. Mitigating bias in machine learning for medicine. Patterns. 2021;2(8):100308. 10.1038/s43856-021-00028-w