Whole slide imaging-based deep learning to predict the treatment response of patients with non-small cell lung cancer.

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第一作者： Yuteng,Pan

第一单位： Medical Science and Technology Innovation Center, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.

作者： Yuteng,Pan ^[1] ; Wei,Sheng ^[2] ; Liting,Shi ^[3] ; Di,Jing ^[2] ; Wei,Jiang ^[4] ; Jyh-Cheng,Chen ^[5] ; Haiyan,Wang ^[6] ; Jianfeng,Qiu ^[7]

作者单位： Medical Science and Technology Innovation Center, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China. ^[1] Medical Engineering and Technology Research Center, School of Radiology, Shandong First Medical University and Shandong Academy of Medical Sciences, Tai'an, China. ^[2] Department of Radiation Oncology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China. ^[3] Department of Oncology, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China. ^[4] Department of Radiotherapy, Yantai Yuhuangding Hospital, Qingdao University School of Medicine, Yantai, China. ^[5] Department of Biomedical Imaging and Radiological Sciences National Yang-Ming Chiao-Tung University, Taipei. ^[6] Department of Biomedical Imaging and Radiological Science, China Medical University, Taichung. ^[7] Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China. ^[8]

关键词 Non-small cell lung cancer (NSCLC)chemotherapy and radiotherapy (CRT)deep learning (DL)treatment response whole slide imaging (WSI)

DOI 10.21037/qims-22-1098

PMID 37284119

发布时间 2023-06-08

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