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Skip search results from other journals and go to results- 576 Journal of Medical Internet Research
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Large Language Model Applications for Health Information Extraction in Oncology: Scoping Review
The LLMs for data extraction were commonly applied in pan-cancer clinical settings (n=11, 46%), followed by breast (n=4, 17%), lung (n=4, 17%), neurological (n=2, 8%), colorectal (n=1, 4%), gynecological (n=1, 4%), and liver (n=1, 4%) cancer contexts. The author teams of these studies belonged to institutions in the United States (n=11, 46%), China (n=4, 17%), Korea (n=3, 12%), Germany (n=2, 8%), Spain (n=2, 8%), the United Kingdom (n=1, 4%), and Singapore (n=1, 4%).
JMIR Cancer 2025;11:e65984
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The author affiliation information has been changed from:
Wen Sun1, MSc; Jingwei He1, MSc; Wenqin Wang1, MSc; Chen Lu1, Ph D; Yating Lin1, BSc; Yalan Dou2, Ph D; Weili Yan2, Ph D; Jian Yu1, Ph D
1 Department of Rehabilitation, Children’s Hospital of Fudan University, National Children’s Medical Center, Shanghai, China.
2 Department of Clinical Epidemiology and Clinical Trial Unit, National Children’s Medical Center, Children’s Hospital of Fudan University, Shanghai, China.
to:
Wen Sun1*, MSc; Jingwei He1*, MSc; Wenqin
JMIR Res Protoc 2025;14:e74014
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The SCeiP Model for Remote Rehabilitation in Homebound Patients With Coronary Heart Disease
J Med Internet Res 2025;27:e69927
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