病态的
肾损伤
计算机科学
缺血
医学
急性肾损伤
参数化模型
缺血性损伤
参数统计
肾
人工智能
放射科
病理
心脏病学
内科学
统计
数学
作者
Lihua Chen,Yan Ren,Yizhong Yuan,Jipan Xu,Baole Wen,Shuangshuang Xie,Jinxia Zhu,Wenshuo Li,Xiaoli Gong,Wen Shen
标识
DOI:10.1186/s12880-024-01320-6
摘要
Renal cold ischemia-reperfusion injury (CIRI), a pathological process during kidney transplantation, may result in delayed graft function and negatively impact graft survival and function. There is a lack of an accurate and non-invasive tool for evaluating the degree of CIRI. Multi-parametric MRI has been widely used to detect and evaluate kidney injury. The machine learning algorithms introduced the opportunity to combine biomarkers from different MRI metrics into a single classifier.
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