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This position paper argues that medical AI currently neglects real treatment outcomes in training and evaluation, hindering its ability to improve patient care, and recommends incorporating actual outcome data to align with evidence-based medicine principles.
This article argues that observational evidence is underappreciated compared to randomized controlled trials, using historical examples from the 18th century to illustrate its efficiency and power.