Medical large language model for diagnostic reasoning across specialties

IF 50 1区 医学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Nature Medicine Pub Date : 2025-01-31 DOI:10.1038/s41591-025-03520-1
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Abstract

We developed a medical large language model with 176 billion parameters and fine-tuned it to learn physicians’ inferential diagnosis. We showed that the model accurately diagnoses common and rare diseases across specialties, aligns with medical standards, and can be integrated into clinical workflows to effectively enhance physician diagnostic performance.

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用于跨专业诊断推理的医学大语言模型
我们开发了一个有1760亿个参数的医学大语言模型,并对其进行了微调,以学习医生的推理诊断。我们的研究表明,该模型可以准确地诊断跨专业的常见和罕见疾病,符合医疗标准,并且可以集成到临床工作流程中,有效地提高医生的诊断绩效。
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来源期刊
Nature Medicine
Nature Medicine 医学-生化与分子生物学
CiteScore
100.90
自引率
0.70%
发文量
525
审稿时长
1 months
期刊介绍: Nature Medicine is a monthly journal publishing original peer-reviewed research in all areas of medicine. The publication focuses on originality, timeliness, interdisciplinary interest, and the impact on improving human health. In addition to research articles, Nature Medicine also publishes commissioned content such as News, Reviews, and Perspectives. This content aims to provide context for the latest advances in translational and clinical research, reaching a wide audience of M.D. and Ph.D. readers. All editorial decisions for the journal are made by a team of full-time professional editors. Nature Medicine consider all types of clinical research, including: -Case-reports and small case series -Clinical trials, whether phase 1, 2, 3 or 4 -Observational studies -Meta-analyses -Biomarker studies -Public and global health studies Nature Medicine is also committed to facilitating communication between translational and clinical researchers. As such, we consider “hybrid” studies with preclinical and translational findings reported alongside data from clinical studies.
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