Eliminating Bias from Healthcare AI Critical to Improve Health Equity
Algorithms must be tested and continually monitored to assess impact of bias
Artificial intelligence (AI)-driven healthcare has potential to transform medical decision-making and treatment, but AI algorithms must be thoroughly tested and continuously monitored to avoid unintended consequences to patients. In JAMA Network Open, Regenstrief Institute President Peter Embí, M.D., calls for algorithmovigilance (a term he coined for scientific methods and activities relating to evaluation, monitoring, understanding and prevention of adverse effects of algorithms in healthcare) to address inherent biases in healthcare algorithms and their deployment. Image courtesy of Regenstrief Institute
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IMAGE: Artificial intelligence (AI)-driven healthcare has potential to transform medical decision-making and treatment, but AI algorithms must be thoroughly tested and continuously monitored to avoid unintended consequences to patients. In. view more
Credit: Regenstrief Institute
INDIANAPOLIS Artificial intelligence (AI)-driven healthcare has the potential to transform medical decision-making and treatment, but these algorithms must be thoroughly tested and continuously monitored to avoid unintended consequences to patients.
In a
JAMA Network Open Invited Commentary, Regenstrief Institute President and Chief Executive Officer and Indiana University School of Medicine Associate Dean for Informatics and Health Services Research Peter Embí, M.D., M.S., strongly stated the importance of algorithmovigilance to address inherent biases in healthcare algorithms and their deployment. Algorithmovigilance, a term coined by Dr. Embí, can be defined as the scient