Lack of diverse datasets in AI research puts patients at risk, experts suggest
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New research published in PLOS Digital Health is calling attention to disparities in artificial intelligence that could inhibit its ability to be effectively deployed in clinical settings.
Researchers analyzed more than 30,000 artificial intelligence clinical papers published in PubMed in 2019 and found that more than 50% of AI studies utilized databases from the U.S. or China, and that almost all the top 10 databases and author nationalities were from high income countries. Such homogenous datasets, the authors explained, can create research bias that hinders the clinical efficacy of AI…
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