Evaluating Locally Run Large Language Models for Obstructive Sleep Apnea Diagnosis and Treatment: A Real-World Polysomnography Study

Although locally run LLMs bypass data security constraints and show promising potential for clinical practice, their performance needs significant improvement prior to real-world implementation. Therefore, at present, the routine implementation of locally run LLMs in sleep medicine needs more refinement and fine tuning before they can be used for interpretation of real-world PSG results.

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Publication Details

Journal
Nature and Science of Sleep
Published
2025-07-01
DOI
https://doi.org/10.2147/nss.s536823
Primary Topic
Obstructive Sleep Apnea Research
Type
article
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article

Evaluating Locally Run Large Language Models for Obstructive Sleep Apnea Diagnosis and Treatment: A Real-World Polysomnography Study

Katharina Bahr‐Hamm, Jonas Eckrich, Tilman Huppertz, Christoph Raphael Buhr et al.
1 links
Nature and Science of Sleep
Obstructive Sleep Apnea Research
article

Evaluating Locally Run Large Language Models for Obstructive Sleep Apnea Diagnosis and Treatment: A Real-World Polysomnography Study

Katharina Bahr‐Hamm, Jonas Eckrich, Tilman Huppertz, Christoph Raphael Buhr, Christopher Seifen, Sebastian Kühn, Johannes Pordzik, Haralampos T Gouveris, Andrew Blaikie, Harry A. Smith, Tom Kelsey, Christoph Matthias
article en

Abstract

Although locally run LLMs bypass data security constraints and show promising potential for clinical practice, their performance needs significant improvement prior to real-world implementation. Therefore, at present, the routine implementation of locally run LLMs in sleep medicine needs more refinement and fine tuning before they can be used for interpretation of real-world PSG results.

Nature and Science of SleepVol. Volume 17
Philipps University of Marburg (DE), University of St Andrews (GB), Johannes Gutenberg University Mainz (DE), Universitätsklinikum Gießen und Marburg (DE), University Medical Center of the Johannes Gutenberg University Mainz (DE)
Quality Education
Openalex Percentile: Top 78%
Obstructive Sleep Apnea Research
DOIOpen Access PDFOpenAlex
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Evaluating Locally Run Large Language Models for Obstructive Sleep Apnea Diagnosis and Treatment: A Real-World Polysomnography Study — Katharina Bahr‐Hamm, Jonas Eckrich, et al. · Nature and Science of Sleep (2025) | TGRS Research Map | TGRS