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Out-of-the-Box Large Language Models for Detecting and Classifying Critical Findings in Radiology Reports Using Various Prompt Strategies
Ish Talati, Juan Manuel Zambrano Chaves, Avisha Das, Imon Banerjee, Daniel L. Rubin
Stanford University Microsoft (United States) Mayo Clinic in Arizona Mayo Clinic Hospital
来源American Journal of Roentgenology
年份2025
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. The study shows a role of contemporary general-purpose models in adapting to specialized medical tasks using minimal data annotation.
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Artificial Intelligence in Healthcare and Education · Biomedical Text Mining and Ontologies
参考文献 11
The Malpractice Liability of Radiology Reports: Minimizing the Risk
被引 71Aparna Srinivasa Babu, Michael Brooks · Radiographics · 2015
Assessment of actionable findings in radiology reports
被引 12Jacob J. Visser, Marianne de Vries, Jan A. Kors · European Journal of Radiology · 2020
Between Always and Never: Evaluating Uncertainty in Radiology Reports Using Natural Language Processing
被引 35Andrew L. Callen, Sara M. Dupont, Adi Price · Journal of Imaging Informatics in Medicine · 2020
此处列出前 3 条
引用本文 6
Large-Scale Large Language Model (LLM)-Assisted Report Mining for Elbow Tendon Co-occurrence Epidemiology: Prevalence, Association, and Validation
被引 0Kian A Huang, Sonia V Prakash, Haris K Choudhary · Cureus · 2026
Implementation of a Locally Deployed Qwen2.5-7B-Instruct Pipeline for Structured Classification of Elbow MRI Reports
被引 0Kian A Huang, Sonia V Prakash, David Samvelian · Cureus · 2026
From Findings to Impression: Development and Validation of a Section-Aware Framework for Concept Selection in Radiology Reports (Preprint)
被引 0Li Lin, Tian Jiang, Xi Chen · 2026
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