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A novel interpretable machine learning framework integrating clinicopathological and radiomic features for early recurrence prediction in mass-forming intrahepatic cholangiocarcinoma.

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Title: A novel interpretable machine learning framework integrating clinicopathological and radiomic features for early recurrence prediction in mass-forming intrahepatic cholangiocarcinoma.
Authors: Deng XL; Department of Radiology, The First People's Hospital of Yulin, Yulin, Guangxi Zhuang Autonomous Region, 537000, People's Republic of China.; Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China., Yang C; Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China.; Department of Radiology, Guangxi Hospital Division of the First Affiliated Hospital, Sun-Yat-Sen University, Nanning, Guangxi Zhuang Autonomous Region, 530022, People's Republic of China., Qin LH; Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China., Lin XF; Department of Radiology, The First People's Hospital of Yulin, Yulin, Guangxi Zhuang Autonomous Region, 537000, People's Republic of China.; Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China., Zhong F; Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China., Liao JY; Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China. liaojinyuan@gxmu.edu.cn.; Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China. liaojinyuan@gxmu.edu.cn.
Source: Cancer imaging : the official publication of the International Cancer Imaging Society [Cancer Imaging] 2026 Jan 09; Vol. 26 (1), pp. 23. Date of Electronic Publication: 2026 Jan 09.
Publication Type: Journal Article
Journal Info: Publisher: Springer Nature Country of Publication: England NLM ID: 101172931 Publication Model: Electronic Cited Medium: Internet ISSN: 1470-7330 (Electronic) Linking ISSN: 14707330 NLM ISO Abbreviation: Cancer Imaging Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: A novel interpretable machine learning framework integrating clinicopathological and radiomic features for early recurrence prediction in mass-forming intrahepatic cholangiocarcinoma.
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  Data: <searchLink fieldCode="AU" term="%22Deng+XL%22">Deng XL</searchLink>; Department of Radiology, The First People's Hospital of Yulin, Yulin, Guangxi Zhuang Autonomous Region, 537000, People's Republic of China.; Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China.<br /><searchLink fieldCode="AU" term="%22Yang+C%22">Yang C</searchLink>; Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China.; Department of Radiology, Guangxi Hospital Division of the First Affiliated Hospital, Sun-Yat-Sen University, Nanning, Guangxi Zhuang Autonomous Region, 530022, People's Republic of China.<br /><searchLink fieldCode="AU" term="%22Qin+LH%22">Qin LH</searchLink>; Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China.<br /><searchLink fieldCode="AU" term="%22Lin+XF%22">Lin XF</searchLink>; Department of Radiology, The First People's Hospital of Yulin, Yulin, Guangxi Zhuang Autonomous Region, 537000, People's Republic of China.; Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China.<br /><searchLink fieldCode="AU" term="%22Zhong+F%22">Zhong F</searchLink>; Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China.<br /><searchLink fieldCode="AU" term="%22Liao+JY%22">Liao JY</searchLink>; Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China. liaojinyuan@gxmu.edu.cn.; Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China. liaojinyuan@gxmu.edu.cn.
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  Data: <searchLink fieldCode="JN" term="%22101172931%22">Cancer imaging : the official publication of the International Cancer Imaging Society</searchLink> [Cancer Imaging] 2026 Jan 09; Vol. 26 (1), pp. 23. <i>Date of Electronic Publication: </i>2026 Jan 09.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Springer+Nature%22">Springer Nature </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101172931 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1470-7330 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2214707330%22">14707330 </searchLink><i>NLM ISO Abbreviation: </i>Cancer Imaging <i>Subsets: </i>MEDLINE
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        Value: 10.1186/s40644-025-00987-6
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        Text: English
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              Text: 2026 Jan 09
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