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New study aims to reduce bias in AI health prediction models

Rapid advances in Artificial Intelligence (AI) have opened the way for the creation of a huge range of new healthcare tools, but to ensure that these tools do not exacerbate preexisting health inequities, researchers urge the use of more representative data in their development.
United Kingdom Cathie Sudlow Sara Khalid Centre For Ethnic Health Research Scientist At Health Data Research United Kingdom Connectivity National Core Study

One on One ... with Curtis P. Langlotz, MD, PhD

Stanford University Professor of Radiology, Medicine and Biomedical Data Science; Director of the Center for Artificial Intelligence in Medicine and  Imaging (AIMI Center); Associate Director of Stanford’s Institute for Human-Centered Artificial Intelligence (HAI); and Associate Chair for Information Systems, Medical Informatics Director for Stanford Health Care  
United States Curtis Langlotz Curtisp Langlotz Steering Committee Nuance Communications American Medical Informatics Association

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