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A clinician and patient interact with artificial intelligence (AI)–based decision support that provides information about, for example, the likelihood of a diagnosis, utility of a treatment, or a prognosis. Even if the algorithm is unbiased, clinician-, patient-, and social-level factors can influence how the recommendations are interpreted and implemented, which can result in latent treatment bias.
