Bias, Fairness and Generalizability
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Description
Dr. Leo Celi discusses various problems involving bias, fairness and generalizability that continue to affect the adoption of artificial intelligence models in hospitals and clinics.  Dr. Celi also makes a number of recommendations for improving relationships between health care organizations and the private sector as AI research moves forward. Articles that Dr. Celi mentions in the podcast are: Futoma J, Simons M, Panch T, Doshi-Velez F, Celi L.  The myth of generalizability in clinical research and machine learning in health care.  Lancet Digital Health 2020; 2:e489-92.  At:  https://www.thelancet.com/journals/landig/article/PIIS2589-7500(20)30186-2/fulltext. Stuppe A, Singerman D, Celi L.  The reproducibility crisis in the age of digital medicine.  NPJ Digital Medicine January 29, 2019.  At https://www.nature.com/articles/s41746-019-0079-z. Vyas D, Eisenstein L, Jones D.  Hidden in plain sight—reconsidering the use of race correction in clinical algorithms.  The New England Journal of Medicine August 27, 2020; 383(9):874-882.  At: https://www.nejm.org/doi/full/10.1056/NEJMms2004740.
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