SOURCE-LINKED INTELLIGENCE

Misaligned Clinical Risk Classification and Cost Asymmetry in Open-Weight Large Language Models

arXiv · AI, language, vision and robotics · article · Sep 21, 2026 · UTC

How large language models (LLMs) integrate patient risk with clinical cost tradeoffs remains poorly understood. We investigated how four open-weight LLMs (Qwen-2.5-7B/32B and Llama-3.1-8B/70B) internally represent cost tradeoffs, how these representations relate to clinical predictions, and whether decisions shift as predicted by the specified cost direction and magnitude. Using a public diabetes dataset, we varied 11 false-negative (FN) to false-positive (FP) cost ratios across three phrasings and examined representations and behavioral outputs. Patient risk was linearly recoverable on par wi

Read original source ↗ Open in workspace

recordType

paper

region

Global