基于机器学习构建肿瘤相关静脉血栓栓塞风险预测模型的研究进展  

Research progress on machine learning based risk prediction model for cancer-associated thrombosis

作　　者：徐梅 林雯雯 宁丽[2] 王莉[2] 夏云 Xu Mei;Lin Wenwen;Ning Li;Wang Li;Xia Yun(School of Nursing,Zhejiang Chinese Medical University,Hangzhou 310053,China;Nursing Department,Affiliated Hangzhou First People's Hospital,Hangzhou 310006,China;Nursing Department,Hangzhou Cancer Hospital,Hangzhou 310002,China)

机构地区：[1]浙江中医药大学护理学院,杭州310053 [2]杭州市第一人民医院护理部,杭州310006 [3]杭州市肿瘤医院护理部,杭州310002

出　　处：《中华现代护理杂志》2024年第31期4302-4307,共6页Chinese Journal of Modern Nursing

基　　金：浙江省基础公益研究计划项目(LGF22H160079);浙江省医药卫生科技计划项目(2023KY192)。

摘　　要：静脉血栓栓塞症是癌症患者的常见并发症,也是导致癌症患者死亡的常见原因。机器学习算法为肿瘤相关静脉血栓栓塞(CAT)风险评估提供了新途径。本文对机器学习算法在CAT风险预测模型的研究进展进行综述,从模型的构建方法、基本情况和预测性能等方面进行总结、分析和比较,以期为今后CAT风险预测模型的构建和应用提供借鉴。Venous thromboembolism is a common complication in cancer patients and a common cause of death in cancer patients.Machine learning algorithms provide a new approach for assessing the risk of cancer-associated thrombosis(CAT).This paper reviews the machine learning based risk prediction model for CAT from summarizing,analyzing,and comparing the construction methods,basic information,and predictive performance of the models,so as to provide reference for the construction and application of CAT risk prediction models.

关 键 词：综述 静脉血栓栓塞症 机器学习 肿瘤 肿瘤相关静脉血栓栓塞症 风险预测模型 

分 类 号：R473.73[医药卫生—护理学]