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. |
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| 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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| ISSN: | 1478-3231 |
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| DOI: | 10.1111/liv.15870 |
