cirpublications.com-LvVZ-1790878255-o260431135 1790878255 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 2023 2 2 Sanjay Kulkarni Meenal Joshi Rohan Patil Aniket Deshmukh 2023 10.68159/o260431135 https://cirpublications.com/pub/journal/1/article/o260431135 Char DS, Shah NH, Magnus D. Implementing machine learning in health care - addressing ethical challenges. N Engl J Med. 2018;378(11):981-3. 10.1056/NEJMp1714229 Price WN, Gerke S, Cohen IG. Potential liability for physicians using artificial intelligence. JAMA. 2019;322(18):1765-6. 10.1001/jama.2019.15064 Vayena E, Blasimme A, Cohen IG. Machine learning in medicine: Addressing ethical challenges. PLoS Med. 2018;15(11):e1002689. 10.1371/journal.pmed.1002689 Mittelstadt B. Principles alone cannot guarantee ethical AI. Nat Mach Intell. 2019;1(11):501-7. 10.1038/s42256-019-0114-4 Gerke S, Babic B, Evgeniou T, Cohen IG. The need for a system view to regulate artificial intelligence/machine learning-based software as medical device. NPJ Digit Med. 2020;3:53. 10.1038/s41746-020-0262-2 Cohen IG, Evgeniou T, Gerke S, Minssen T. The European artificial intelligence strategy: implications and challenges for digital health. Lancet Digit Health. 2020;2(7):e376-e379. 10.1016/S2589-7500(20)30112-6 Fenech ME, Buston O. AI in Cardiac Imaging: A UK-Based Perspective on Addressing Governance, Ethics, and Data Protection. J Med Artif Intell. 2019;2:15. 10.21037/jmai.2019.08.02 Geis JR, Brady A, Wu CC, Spencer J, Ranschaert E, Jaremko JL, et al. Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement. Radiology. 2019;293(2):436-40. 10.1148/radiol.2019191586 Larson DB, Magnus DC, Lungren MP, Shah NH, Langlotz CP. Ethics of using and sharing clinical imaging datasets for artificial intelligence: a perspective from the RSNA ethics of AI in radiology committee. Radiol Artif Intell. 2020;2(2):e190269. 10.1148/ryai.2020190269 Challen R, Denny J, Pitt M, Gompels L, Edwards T, Tsaneva-Atanasova K. Artificial intelligence, bias and clinical safety. BMJ Qual Saf. 2019;28(3):231-7. 10.1136/bmjqs-2018-008370 Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019;25(1):44-56. 10.1038/s41591-018-0300-7 Wiens J, Saria S, Sendak M, Ghassemi M, Liu VX, Das R, 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 Rajkomar A, Hardt M, Howell MD, Corrado G, Chin MH. Ensuring fairness in machine learning to advance health equity. Ann Intern Med. 2018;169(12):866-72. 10.7326/M18-1990 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 Reddy S, Fox J, Purohit MP. Artificial intelligence-enabled healthcare delivery. J R Soc Med. 2019;112(1):22-8. 10.1177/0141076818816910 Meskó B, Hetényi G, Győrffy Z. Will artificial intelligence solve the human resource crisis in healthcare? BMC Health Serv Res. 2018;18(1):545. 10.1186/s12913-018-3359-4 Chen IY, Szolovits P, Ghassemi M. Can AI help reduce disparities in general medical and mental health care? AMA J Ethics. 2019;21(2):E167-79. 10.1001/amajethics.2019.167 Nebeker C, Torous J, Bartlett Ellis RJ. Building the case for actionable ethics in digital health research supported by artificial intelligence. BMC Med. 2019;17(1):137. 10.1186/s12916-019-1377-7 Rigby MJ. Ethical dimensions of using artificial intelligence in health care. AMA J Ethics. 2019;21(2):E121-4. 10.1001/amajethics.2019.121 Martinez-Martin N, Insel TR, Dagum P, Greely HT, Cho MK. Data mining for health: staking out the ethical territory of digital phenotyping. NPJ Digit Med. 2018;1:68. 10.1038/s41746-018-0075-8 Panch T, Mattie H, Celi LA. The “inconvenient truth” about AI in healthcare. NPJ Digit Med. 2019;2:77. 10.1038/s41746-019-0155-4 Jaremko JL, Azar M, Bromwich R, Lum W, Cheong L, Gibert M, et al. Canadian Association of Radiologists white paper on ethical and legal issues related to artificial intelligence in radiology. Can Assoc Radiol J. 2019;70(2):107-18. 10.1016/j.carj.2019.03.003 Brady AP. Error and discrepancy in radiology: inevitable or avoidable? Insights Imaging. 2017;8(1):171-82. 10.1007/s13244-016-0534-1 Pesapane F, Codari M, Sardanelli F. Artificial intelligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine. Eur Radiol Exp. 2018;2(1):35. 10.1186/s41747-018-0061-6 Rajpurkar P, Chen PJ, Ng AY, Lungren MP. Deep learning in radiology: now the real work begins. J Biomed Inform. 2019;89:1-2. 10.1016/j.jbi.2018.11.009 Langlotz CP. Will artificial intelligence replace radiologists? Radiol Artif Intell. 2019;1(3):e190058. 10.1148/ryai.2019190058 Pesapane F, Volonté C, Codari M, Sardanelli F. Artificial intelligence as a medical device in radiology: ethical and regulatory issues in Europe and the United States. Insights Imaging. 2018;9(5):745-53. 10.1007/s13244-018-0649-y Thrall JH, Li X, Li Q, Cruz C, Do S, Dreyer K, et al. Artificial intelligence and machine learning in radiology: opportunities, challenges, pitfalls, and criteria for success. J Am Coll Radiol. 2018;15(3 Pt B):504-8. 10.1016/j.jacr.2017.12.026 Kohli A, Mahajan V, Seals JK, Klein A. Concepts in US Food and Drug Administration Oversight of Artificial Intelligence for Medical Imaging. AJR Am J Roentgenol. 2021;216(4):885-7. 10.2214/AJR.20.24678