使用微调的大型语言模型对脑MRI报告进行自动分类
Jun Kanzawa1, Koichiro Yasaka2, Nana Fujita1
1Department of Radiology, The University of Tokyo Hospital, Tokyo, Japan.
Neuroradiology
|July 12, 2024
概括
微调的大型语言模型 (LLM) 在分类大脑MRI报告中显示了与放射科医生相似的准确性. 这些人工智能模型显著减少了分类时间,为医学图像分析提供了更快的替代方案.
科学领域:
- 放射学中的人工智能
- 医学自然语言处理 医学自然语言处理
- 大脑MRI分析 分析
背景情况:
- 对脑磁共振成像 (MRI) 报告的准确分类对于治疗计划至关重要.
- 放射科医生的手动分类是耗时的,并且会有变化.
- 大型语言模型 (LLM) 显示了自动化复杂医疗文本分析的潜力.
研究的目的:
- 评估微调的LLM在分类大脑MRI报告中的有效性.
- 在这个分类任务中,比较LLM与人类放射科医生的表现.
- 评估基于LLM的分类的时间效率.
主要方法:
- 一项回顾性研究利用了大数据集的大脑MRI报告 (759次培训,284次验证,164次测试).
- 一个来自变压器的双向编码器表示 (BERT) 日本模型被微调以分类为非瘤,治疗后瘤和治疗前瘤类别.
- 模型的性能与测试数据集中的两个独立放射科医生进行了对比评估.
主要成果:
- 精心调整的LLM实现了0.970的整体准确度,在所有组中具有高灵敏度和特异性.
- 在LLM和人类阅读器之间没有观察到准确性,灵敏性或特异性的统计学上显著差异 (p ≥0.371).
- 该LLM分类报告比放射科医生快20-26倍.
结论:
- 精心调整的LLM在分类大脑MRI报告方面表现相当于放射科医生.
- 在这项诊断任务中,LLM提供了相当大的节省时间的优势.
- 这项技术有望提高放射学工作流程的效率.
相关概念视频
Magnetic Resonance Imaging
Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
Imaging Studies I: CT and MRI
Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
Description of the Procedures
Computed Tomography (CT) scan:
Computed Tomography (CT) scans use X-ray technology to generate detailed images of bones, organs, and tissues. During the scan, the patient lies on a moving table...
Description of the Procedures
Computed Tomography (CT) scan:
Computed Tomography (CT) scans use X-ray technology to generate detailed images of bones, organs, and tissues. During the scan, the patient lies on a moving table...
Brain Imaging
Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and Transcranial Magnetic Stimulation (TMS).
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and Transcranial Magnetic Stimulation (TMS).
Imaging Studies IV: Magnetic Resonance Imaging
Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...


