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您的检索式：作者名="In Neng Chan"
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| 1 | Deep learning based radiomics for gastrointestinal cancer diagnosis and treatment:A minireview显示文摘Gastrointestinal(GI)cancers are the major cause of cancer-related mortality globally.Medical imaging is an important auxiliary means for the diagnosis,assessment and prognostic prediction of GI cancers.Radiomics is an emerging and effective technology to decipher the encoded information within medical images,and traditional machine learning is the most commonly used tool.Recent advances in deep learning technology have further promoted the development of radiomics.In the field of GI cancer,although there are several surveys on radiomics,there is no specific review on the application of deep-learning-based radiomics(DLR).In this review,a search was conducted on Web of Science,PubMed,and Google Scholar with an emphasis on the application of DLR for GI cancers,including esophageal,gastric,liver,pancreatic,and colorectal cancers.Besides,the challenges and recommendations based on the findings of the review are comprehensively analyzed to advance DLR. | Pak Kin Wong In Neng Chan Hao-Ming Yan Shan Gao Chi Hong Wong Tao Yan Liang Yao Ying Hu Zhong-Ren Wang Hon Ho Yu | 2022 | World Journal of Gastroenterology2022，28，45： | 1 |
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