Clinical Decision-Making
Overview
Clinical decision-making is the process of choosing tests, diagnoses, treatments, and care plans from evidence that may be incomplete or uncertain, with consequences for patient outcomes and resource use. Approaches include clinical prediction models, causal and individualized treatment-effect methods, decision-focused optimization, and sequential policies that balance gathering more information against acting or deferring. Large language models and multi-agent systems are increasingly evaluated for interactive tasks such as history-taking, triage, longitudinal record review, and treatment planning, often with retrieval, uncertainty estimates, or clinician oversight. A central challenge is that strong diagnostic or benchmark scores do not ensure safe, stable, fair decisions in real workflows, especially when evidence is missing, patient context shifts, or the costs of errors differ.
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