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Multitask deep learning for prediction of microvascular invasion and recurrence-free survival in hepatocellular carcinoma based on MRI images.

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Title: Multitask deep learning for prediction of microvascular invasion and recurrence-free survival in hepatocellular carcinoma based on MRI images.
Authors: Wang F; Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China., Zhan G; College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Japan., Chen QQ; Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China., Xu HY; Department of Radiology, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, China., Cao D; Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.; Department of Radiology, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, China., Zhang YY; School of Medicine, Shaoxing University, Shaoxing, China., Li YH; College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Japan., Zhang CJ; Research Center for Healthcare Data Science, Zhejiang Lab, Hangzhou, China., Jin Y; Department of Radiology, Ningbo Medical Center Li Huili Hospital, Ningbo, China., Ji WB; Department of Radiology, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, China., Ma JB; Department of Radiology, The First Hospital of Jiaxing, The Affiliated Hospital of Jiaxing University, Jiaxing, China., Yang YJ; Department of Radiology, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China., Zhou W; Department of Radiology, Huzhou Central Hospital, Affiliated to Huzhou University, Huzhou, China., Peng ZY; Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China., Liang X; Department of General Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China., Deng LP; Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China., Lin LF; College of Computer Science and Technology, Zhejiang University, Hangzhou, China., Chen YW; College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Japan., Hu HJ; Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.; Medical Imaging International Scientific and Technological Cooperation Base of Zhejiang Province, Hangzhou, China.
Source: Liver international : official journal of the International Association for the Study of the Liver [Liver Int] 2024 Jun; Vol. 44 (6), pp. 1351-1362. Date of Electronic Publication: 2024 Mar 04.
Publication Type: Journal Article; Multicenter Study; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Wiley-Blackwell Country of Publication: United States NLM ID: 101160857 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1478-3231 (Electronic) Linking ISSN: 14783223 NLM ISO Abbreviation: Liver Int Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Multitask deep learning for prediction of microvascular invasion and recurrence-free survival in hepatocellular carcinoma based on MRI images.
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  Data: <searchLink fieldCode="AU" term="%22Wang+F%22">Wang F</searchLink>; Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.<br /><searchLink fieldCode="AU" term="%22Zhan+G%22">Zhan G</searchLink>; College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Japan.<br /><searchLink fieldCode="AU" term="%22Chen+QQ%22">Chen QQ</searchLink>; Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.<br /><searchLink fieldCode="AU" term="%22Xu+HY%22">Xu HY</searchLink>; Department of Radiology, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, China.<br /><searchLink fieldCode="AU" term="%22Cao+D%22">Cao D</searchLink>; Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.; Department of Radiology, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, China.<br /><searchLink fieldCode="AU" term="%22Zhang+YY%22">Zhang YY</searchLink>; School of Medicine, Shaoxing University, Shaoxing, China.<br /><searchLink fieldCode="AU" term="%22Li+YH%22">Li YH</searchLink>; College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Japan.<br /><searchLink fieldCode="AU" term="%22Zhang+CJ%22">Zhang CJ</searchLink>; Research Center for Healthcare Data Science, Zhejiang Lab, Hangzhou, China.<br /><searchLink fieldCode="AU" term="%22Jin+Y%22">Jin Y</searchLink>; Department of Radiology, Ningbo Medical Center Li Huili Hospital, Ningbo, China.<br /><searchLink fieldCode="AU" term="%22Ji+WB%22">Ji WB</searchLink>; Department of Radiology, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, China.<br /><searchLink fieldCode="AU" term="%22Ma+JB%22">Ma JB</searchLink>; Department of Radiology, The First Hospital of Jiaxing, The Affiliated Hospital of Jiaxing University, Jiaxing, China.<br /><searchLink fieldCode="AU" term="%22Yang+YJ%22">Yang YJ</searchLink>; Department of Radiology, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, China.<br /><searchLink fieldCode="AU" term="%22Zhou+W%22">Zhou W</searchLink>; Department of Radiology, Huzhou Central Hospital, Affiliated to Huzhou University, Huzhou, China.<br /><searchLink fieldCode="AU" term="%22Peng+ZY%22">Peng ZY</searchLink>; Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.<br /><searchLink fieldCode="AU" term="%22Liang+X%22">Liang X</searchLink>; Department of General Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.<br /><searchLink fieldCode="AU" term="%22Deng+LP%22">Deng LP</searchLink>; Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.<br /><searchLink fieldCode="AU" term="%22Lin+LF%22">Lin LF</searchLink>; College of Computer Science and Technology, Zhejiang University, Hangzhou, China.<br /><searchLink fieldCode="AU" term="%22Chen+YW%22">Chen YW</searchLink>; College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Japan.<br /><searchLink fieldCode="AU" term="%22Hu+HJ%22">Hu HJ</searchLink>; Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.; Medical Imaging International Scientific and Technological Cooperation Base of Zhejiang Province, Hangzhou, China.
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  Data: <searchLink fieldCode="JN" term="%22101160857%22">Liver international : official journal of the International Association for the Study of the Liver</searchLink> [Liver Int] 2024 Jun; Vol. 44 (6), pp. 1351-1362. <i>Date of Electronic Publication: </i>2024 Mar 04.
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  Data: Journal Article; Multicenter Study; Research Support, Non-U.S. Gov't
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Wiley-Blackwell%22">Wiley-Blackwell </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101160857 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1478-3231 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2214783223%22">14783223 </searchLink><i>NLM ISO Abbreviation: </i>Liver Int <i>Subsets: </i>MEDLINE
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        Value: 10.1111/liv.15870
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        Text: English
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      – TitleFull: Multitask deep learning for prediction of microvascular invasion and recurrence-free survival in hepatocellular carcinoma based on MRI images.
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              Text: 2024 Jun
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