A multicenter multifunctional assessment of large language models in pure-tone audiogram interpretation for patients

No LLMs (Large Language Models) have yet been evaluated for understanding picture reports. Pure-tone audiograms, the gold standard for hearing loss assessment, are technical and often incomprehensible to patients without specialist interpretation. We conducted a blinded, multicenter evaluation of eight LLMs across diagnostic, interpretive, and recommendation tasks using 140 audiogram reports, assessed by clinicians and lay reviewers. The study revealed that DeepSeek-V3 achieved the highest diagnostic accuracy (severity: 67.00% ; type: 54.00%), R1 proved most suitable for general readership (FKGL: 6.41). The general public perceived significant benefits from all models in comprehension and emotional support, with Gemini 2.0 Flash/Thinking scoring higher. Challenges remain in understanding pathological mechanisms and controlling hallucinations. While current general-purpose LLMs cannot replace the diagnostic capabilities of physicians, they may serve as effective auxiliary tools for translating specialized audiogram data into structured, patient-accessible interpretations, with particular relevance for populations facing limited access to hearing-care services.

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Publication Details

Journal
npj Digital Medicine
Published
2026-03-15
DOI
https://doi.org/10.1038/s41746-026-02537-1
Primary Topic
Hearing Loss and Rehabilitation
Type
article
Field-Weighted Citation Impact
0.00

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article

A multicenter multifunctional assessment of large language models in pure-tone audiogram interpretation for patients

Chenghua Tian, Jianbo Lei, Jiuke Huang, Xiaoyi Jiao et al.
npj Digital Medicine
Hearing Loss and Rehabilitation
article

A multicenter multifunctional assessment of large language models in pure-tone audiogram interpretation for patients

Chenghua Tian, Jianbo Lei, Jiuke Huang, Xiaoyi Jiao, Zhengyang Lu, Qichuan Fang, Guixuan Wang, Peng Xiang, Ming Chen, Mengyao Xing, XueMing Leng, Tingting Zhou
article en

Abstract

No LLMs (Large Language Models) have yet been evaluated for understanding picture reports. Pure-tone audiograms, the gold standard for hearing loss assessment, are technical and often incomprehensible to patients without specialist interpretation. We conducted a blinded, multicenter evaluation of eight LLMs across diagnostic, interpretive, and recommendation tasks using 140 audiogram reports, assessed by clinicians and lay reviewers. The study revealed that DeepSeek-V3 achieved the highest diagnostic accuracy (severity: 67.00% ; type: 54.00%), R1 proved most suitable for general readership (FKGL: 6.41). The general public perceived significant benefits from all models in comprehension and emotional support, with Gemini 2.0 Flash/Thinking scoring higher. Challenges remain in understanding pathological mechanisms and controlling hallucinations. While current general-purpose LLMs cannot replace the diagnostic capabilities of physicians, they may serve as effective auxiliary tools for translating specialized audiogram data into structured, patient-accessible interpretations, with particular relevance for populations facing limited access to hearing-care services.

npj Digital Medicine
Zhejiang Chinese Medical University (CN), Southwest Medical University (CN), Affiliated Hospital of Southwest Medical University (CN), Zhejiang Lab (CN), Second Affiliated Hospital of Zhejiang University (CN), Center for Life Sciences (CN), University of Chinese Academy of Sciences (CN), Zhejiang University (CN), Columbia University (US)
National Natural Science Foundation of China, Natural Science Foundation of Zhejiang Province
Quality Education
Openalex Percentile: Top 26%
Hearing Loss and Rehabilitation
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