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Letter to the Editor:From data integration to precision intelligence:The morphological-functional integration pathway of the hepatic alveolar echinococcosis surgical decision system 认领 引用
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作者 Tie Deng Yan-Mei Feng +1 位作者 Chuan-Ming Li Jun-Bang Feng 《World Journal of Gastroenterology》 SCIE CAS 2026年第28期152-156,共5页
A recent study published in the World Journal of Gastroenterology by Zhu et al demonstrates that machine learning can optimize surgical decision-making for hepatic alveolar echinococcosis(HAE).Through SHapley Additive... A recent study published in the World Journal of Gastroenterology by Zhu et al demonstrates that machine learning can optimize surgical decision-making for hepatic alveolar echinococcosis(HAE).Through SHapley Additive exPlanations analysis,the study indicates that the type of vascular invasion is a key determinant in selecting between hepatectomy and ex vivo liver resection and autotransplantation.The model developed by Zhu et al offers a novel approach for precise preoperative assessment of HAE,holding significant clinical value.However,the model relies on the number of involved vessels to assess vascular invasion and uses a single-line measurement for lesion size,which may underestimate surgical risks and introduce subjective bias.Comprehensive preoperative assessment requires integrating multiple parameters,including the depth and extent of vascular involvement,three-dimensional lesion volume,and postoperative residual functional liver volume,all of which directly influence surgical planning and prognosis.Future efforts should focus on integrating multimodal data and leveraging machine learning to develop more comprehensive and objective risk prediction systems.Building upon this foundation,this paper proposes establishing a“morphology-function”integrated preoperative assessment paradigm to advance the precision of surgical decision-making in HAE. 展开更多
关键词 Hepatic alveolar echinococcosis Machine learning Morphology-function Multimodal data Surgical
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