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Medicine study warns of ethical risks in machine-learning application of EHR


A powerful tool, but only as good as its programmer

Newswire: March 15, 2018.

Dateline: Boston.

Machine learning can be a powerful assistant to physicians and healthcare professionals but researchers say advancements in that field pose ethical risks specific to medicine.

In an editorial published this week in the New England Journal of Medicine researchers from the Stanford University School of Medicine say the tremendous growth seen in machine-learning tools demands that physicians and scientists carefully consider the ethics of including that data into decision-making.

Specifically, that involves:

In October, a study by the New York City Department of Health and Mental Hygiene revealed, through the use of electronic records, that physicians were not prescribing to men of color or women a pre-exposure medication that lowers the chances of HIV infection, demonstrating how data can both create a biased clinical recommendation, or expose a pattern.

“Once machine-learning-based decision support is integrated into clinical care, withholding information from electronic records will become increasingly difficult, since patients whose data aren’t recorded can’t benefit from machine-learning analyses,” the current study’s authors wrote.

Read the full story here.

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