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A collective capability boundary in frontier large language models on guideline-conformant and case-specific oncology decision-making
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decision-makingclinical applicationslarge language modelsoncology
2608.28592
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1h ago80%
Abstract
This paper evaluates the decision-making capabilities of frontier large language models in oncology, revealing significant blind spots in guideline-conformant decision-making.
Reality Card
Core Claim
The study found that 42.1% of oncology decision points were answered correctly by none of the evaluated models, highlighting a critical need for architectural changes in LLMs for clinical decision-making.
Method / Result
42.1% of all items were answered correctly by none of the nine models evaluated.
Limitations
The assumption that any single model can be the sole basis for a clinical decision limits reproducibility and effectiveness.
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