Open Access
| Issue |
BIO Web Conf.
Volume 200, 2025
Biology, Health & Artificial Intelligence Conference (BHAI 2025)
|
|
|---|---|---|
| Article Number | 01007 | |
| Number of page(s) | 12 | |
| DOI | https://doi.org/10.1051/bioconf/202520001007 | |
| Published online | 05 December 2025 | |
- Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019 Jan;25(1):44–56. [CrossRef] [PubMed] [Google Scholar]
- Esteva A, Robicquet A, Ramsundar B, Kuleshov V, DePristo M, Chou K, Cui C, Corrado G, Thrun S, & Dean J. A guide to deep learning in healthcare. Nat Med. 2019 Jan;25(1):24–29. [Google Scholar]
- Obermeyer Z, Powers B, Vogeli C, Mullainathan S. Dissecting racial bias in an algorithm used to manage the health of populations. Science [Internet]. 24 oct 2019 ; 366(6464) : 447–53. https://doi.org/10.1126/science.aax2342 [CrossRef] [PubMed] [Google Scholar]
- Amann J, Blasimme A, Vayena E, Frey D, Madai VI. Explainability for artificial intelligence in healthcare : a multidisciplinary perspective. BMC Medical Informatics And Decision Making [Internet]. 30 nov 2020 ; 20(1). https://doi.org/10.1186/s12911-020-01332-6 [Google Scholar]
- World Health Organization. Ethics and governance of artificial intelligence for health: WHO guidance. Geneva: World Health Organization; 2021. https://www.who.int/publications/i/item/9789240029200 [Google Scholar]
- Grote T, Berens P. On the ethics of algorithmic decision-making in healthcare. J Med Ethics. 2020 Mar;46(3):205–211. https://doi.org/10.1136/medethics-2019-105586 [Google Scholar]
- Jobin A, Ienca M, Vayena E. The global landscape of AI ethics guidelines. Nat Mach Intell. 2019 Sep;1(9):389–399. [Google Scholar]
- Kingdom of Morocco. Law No. 09-08 enacted by Dahir No. 1-09-15 of 18 February 2009 on the protection of individuals with regard to the processing of personal data. Official Bulletin No. 5714. 2009. [Google Scholar]
- Moroccan Order of Physicians. Medical Code of Ethics. 2021. [Google Scholar]
- Mittelstadt B. Principles alone cannot guarantee ethical AI. Nat Mach Intell. 2019 Nov;1(11):501–507. https://doi.org/10.1038/s42256-019-0114-4 [Google Scholar]
- Ploug T, Holm S. The four dimensions of contestable AI diagnostics A patient-centric approach to explainable AI. Artif Intell Med. 2020 Jul;107:101901. https://doi.org/10.1016/j.artmed.2020.101901 [Google Scholar]
- Morley J, Machado CCV, Burr C, Cowls J, Joshi I, Taddeo M, et al. The ethics of AI in health care: A mapping review. Soc Sci Med. 2020 Sep;260:113172. https://doi.org/10.1016/j.socscimed.2020.113172 [Google Scholar]
- McCoy LG, Nagaraj S, Morgado F, Harish V, Das S, Celi LA. What do medical students actually need to know about artificial intelligence? NPJ Digit Med. 2020 Jun 12;3:86. https://doi.org/10.1038/s41746-020-0294-7 [Google Scholar]
- Geis JR, Brady AP, 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. Radiol Artif Intell. 2019 Nov 27;1(6):e190258. https://doi.org/10.1148/radiol.2019191586 [Google Scholar]
- Diamond IR, Grant RC, Feldman BM, Pencharz PB, Ling SC, Moore AM, et al. Defining consensus: a systematic review recommends methodologic criteria for reporting of Delphi studies. J Clin Epidemiol. 2014 Apr;67(4):401–9. https://doi.org/10.1016/j.jclinepi.2013.12.002 [Google Scholar]
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