Improving Medical Calculation of LLMs with Embedded Coding

arXiv cs.AISeptember 29, 2026en

arXiv cs.AI

AI Global Wire

arXiv:2609.31908v1 Announce Type: new Abstract: Large Language Models (LLMs) perform well on medical examinations and question-answering benchmarks, but remain unreliable on medical calculation tasks that require exact numerical outputs. These calculations support high-stakes decisions such as medication dosing, organ-function assessment, and prognostic scoring, for which even small errors can have serious clinical consequences. We introduce MedCode, a framework that improves medical calculation by training LLMs to generate embedded executable code. Given a clinical context, the model identifies the relevant calculator, extracts its input variables, and produces a script that delegates arith

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