Article

Expert-level validation of AI-generated medical text with scalable language models

2025-07-08

Abstract excerpt

<title>Abstract</title> <p>With the growing use of language models (LMs) in clinical environments, there is an immediate need to evaluate the accuracy and safety of LM-generated medical text. Currently, such evaluation relies solely on manual physician review. However, detecting errors in LM-generated text is challenging because 1) manual review is costly and 2) expert-composed reference outputs are often unavail...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 0390bc99-b7b8-5f70-952b-71d91a38b698
DOI: 10.21203/rs.3.rs-7041107/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Expert-level validation of AI-generated medical text with scalable language modelsDOI 10.21203/rs.3.rs-7041107/v1Read

CLEVER: Clinical Large Language Model Evaluationby Expert ReviewSemantic proximity Read

Beyond Benchmarks: Dynamic, Automatic And Systematic Red-Teaming Agents For Trustworthy Medical Language ModelsSemantic proximity Read

Automated Evaluation of Large Language Model Response Concordance with Human Specialist Responses on Physician-to-Physician eConsult CasesSemantic proximity Read

Language-dependent diagnostic safety of medical AI systems: a cross-lingual benchmarking and prospective clinical studySemantic proximity Read

A Clinically-Informed Framework for Evaluating Vision-Language Models in Radiology Report Generation: Taxonomy of Errors and Risk-Aware MetricSemantic proximity Read

HumanELY: Human evaluation of LLM yield, using a novel web-based evaluation toolSemantic proximity Read

The Unreliable Judges: Assessing Reproducibility and Self-Preference Bias of LLMs as Free-Text EvaluatorsSemantic proximity Read

Systematic Literature Review of LLM-Large Language Model in Medical: Digital Health, Technology and ApplicationsSemantic proximity Read

MedScope: A Lightweight Benchmark of Open-Source Large Language Models for Medical Question AnsweringSemantic proximity Read

A Systematic Review of Testing and Evaluation of Healthcare Applications of Large Language Models (LLMs)Semantic proximity Read

A Review of Large Language Models in Medical Education, Clinical Decision Support, and Healthcare AdministrationSemantic proximity Read

Auditing frontier general-purpose large language models in biomedical tasks: reasoning gains, extraction limits, and benchmark reliabilitySemantic proximity Read