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Fine-Tuned LLMs Accelerate Radiology Reports Without Compromising Quality
A large language model fine-tuned on 1.87 million radiology reports generates clinically equivalent impressions while reducing reporting time by nearly half, according to a multicenter evaluation across 42 Chinese hospitals. Original paper: Fine-Tuned Large Language Models for Automated Radiology Impression Generation: A Multicenter Evaluation. — Radiology. Artificial intelligence. 10.1148/ryai.250714 📄 Read the article
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By MedAI DigestA large language model fine-tuned on 1.87 million radiology reports generates clinically equivalent impressions while reducing reporting time by nearly half, according to a multicenter evaluation across 42 Chinese hospitals. Original paper: Fine-Tuned Large Language Models for Automated Radiology Impression Generation: A Multicenter Evaluation. — Radiology. Artificial intelligence. 10.1148/ryai.250714 📄 Read the article