领域(数学分析)
自然语言处理
计算机科学
人工智能
数学
数学分析
作者
Zachary Huemann,Changhee Lee,Junjie Hu,Steve Y. Cho,Tyler Bradshaw
出处
期刊:Radiology
[Radiological Society of North America]
日期:2023-09-27
卷期号:5 (6): e220281-e220281
被引量:23
摘要
Domain adaptation improved the performance of large language models in predicting Deauville scores in PET/CT reports.Keywords Lymphoma, PET, PET/CT, Transfer Learning, Unsupervised Learning, Convolutional Neural Network (CNN), Nuclear Medicine, Deauville, Natural Language Processing, Multimodal Learning, Artificial Intelligence, Machine Learning, Language Modeling Supplemental material is available for this article. © RSNA, 2023See also the commentary by Abajian in this issue.
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