Machine learning (ML), a form of artificial intelligence using computer algorithms, is often applied in ways we take for granted: Spotify to predict music that people may enjoy, Facebook to suggest friends to tag in photos, and Amazon to identify products to buy. Aside from these quotidian tasks, ML holds the promise of enhancing the delivery of quality health care.1 Recently, ML has been used to create programs capable of distinguishing between images of benign and malignant moles with accuracy similar to that of board-certified dermatologists.2 This technology could greatly assist dermatologists in diagnosing and treating skin diseases, thereby improving patient care. However, if not developed with inclusivity in mind, ML could exacerbate health care disparities in dermatology.
Adamson AS, Smith A. Machine Learning and Health Care Disparities in Dermatology. JAMA Dermatol. 2018;154(11):1247–1248. doi:10.1001/jamadermatol.2018.2348
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