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An explainable clinical-radiomics machine learning model for preoperative prediction of WHO/ISUP nuclear grade in clear cell renal cell carcinoma.

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Title: An explainable clinical-radiomics machine learning model for preoperative prediction of WHO/ISUP nuclear grade in clear cell renal cell carcinoma.
Authors: Li Y; Department of Urology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Qingdao University, Qingdao, China. lyuedoctor@163.com., Lin M; Lanzhou University Second Hospital, Lanzhou University, Lanzhou, China., Sun L; Department of Pulmonary and Critical Care Medicine, Yantaishan Hospital, Yantai, China., Dong C; Department of Urology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Qingdao University, Qingdao, China., Yang J; Department of Urology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Qingdao University, Qingdao, China., Li X; Second Hospital of Shandong University, Weifang, China., Lin Y; Department of Urology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Qingdao University, Qingdao, China., Wu J; The Second Medical College, Binzhou Medical University, Yantai, China., Zhao J; Department of Urology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Qingdao University, Qingdao, China. 597375848@qq.com., Lin C; Department of Urology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Qingdao University, Qingdao, China. chunhua.lin@qdu.edu.cn.
Source: Abdominal radiology (New York) [Abdom Radiol (NY)] 2026 Apr 25. Date of Electronic Publication: 2026 Apr 25.
Publication Type: Journal Article
Journal Info: Publisher: Springer Country of Publication: United States NLM ID: 101674571 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2366-0058 (Electronic) NLM ISO Abbreviation: Abdom Radiol (NY) Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: An explainable clinical-radiomics machine learning model for preoperative prediction of WHO/ISUP nuclear grade in clear cell renal cell carcinoma.
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  Data: <searchLink fieldCode="AU" term="%22Li+Y%22">Li Y</searchLink>; Department of Urology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Qingdao University, Qingdao, China. lyuedoctor@163.com.<br /><searchLink fieldCode="AU" term="%22Lin+M%22">Lin M</searchLink>; Lanzhou University Second Hospital, Lanzhou University, Lanzhou, China.<br /><searchLink fieldCode="AU" term="%22Sun+L%22">Sun L</searchLink>; Department of Pulmonary and Critical Care Medicine, Yantaishan Hospital, Yantai, China.<br /><searchLink fieldCode="AU" term="%22Dong+C%22">Dong C</searchLink>; Department of Urology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Qingdao University, Qingdao, China.<br /><searchLink fieldCode="AU" term="%22Yang+J%22">Yang J</searchLink>; Department of Urology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Qingdao University, Qingdao, China.<br /><searchLink fieldCode="AU" term="%22Li+X%22">Li X</searchLink>; Second Hospital of Shandong University, Weifang, China.<br /><searchLink fieldCode="AU" term="%22Lin+Y%22">Lin Y</searchLink>; Department of Urology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Qingdao University, Qingdao, China.<br /><searchLink fieldCode="AU" term="%22Wu+J%22">Wu J</searchLink>; The Second Medical College, Binzhou Medical University, Yantai, China.<br /><searchLink fieldCode="AU" term="%22Zhao+J%22">Zhao J</searchLink>; Department of Urology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Qingdao University, Qingdao, China. 597375848@qq.com.<br /><searchLink fieldCode="AU" term="%22Lin+C%22">Lin C</searchLink>; Department of Urology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Qingdao University, Qingdao, China. chunhua.lin@qdu.edu.cn.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Springer%22">Springer </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101674571 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2366-0058 (Electronic) <i>NLM ISO Abbreviation: </i>Abdom Radiol (NY) <i>Subsets: </i>MEDLINE
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        Value: 10.1007/s00261-026-05521-1
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        Text: English
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      – TitleFull: An explainable clinical-radiomics machine learning model for preoperative prediction of WHO/ISUP nuclear grade in clear cell renal cell carcinoma.
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              Text: 2026 Apr 25
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