Published in
PLOS Medicine, Public Library of Science
Content
by Silas Ruhrberg Estévez, Dyke Ferber, Mihaela van der Schaar, Jakob Nikolas Kather
Medical artificial intelligence research is shifting from single-task models toward multimodal large language model-based agents for complex clinical workflows, requiring benchmarks that assess clinical reasoning, process safety, and resource stewardship rather than final outputs alone. In this Perspective article, Silas Ruhrberg Estévez and colleagues discuss why, as medical AI research shifts toward multimodal large language model-based agents for complex clinical workflows, benchmarks that assess clinical reasoning, process safety, and resource stewardship—rather than final outputs alone—are required.
Jakob Nikolas Kather
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