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面向乳腺肿瘤的诊前问答系统决策模型构建研究

修订日期：2023-02-07 点此下载全文

引用本文：王世文,李一凡,郑群,等.面向乳腺肿瘤的诊前问答系统决策模型构建研究[J].医学信息学杂志,2023,44(8):54-59, 65

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作者	单位
王世文	天津师范大学管理学院天津 300387
李一凡	天津师范大学管理学院天津 300387
郑群	天津师范大学管理学院天津 300387
曹旭晨	天津医科大学肿瘤医院乳腺一科天津 300181

基金项目:天津市应用基础计划重点项目(项目编号:S18ZC63056)。

中文摘要:目的/意义运用决策树分类模型模拟专家问诊思路,预测潜在或已有乳腺肿瘤患者的疾病风险。方法/过程采用C4.5经典分类算法和悲观剪枝法,对调研收集的病例数据进行患者预问诊的结果预测。结果/结论生成一棵以“术后化疗or放疗在院是否结束”为根节点、拥有76个叶子节点的C4.5决策树,预测准确率达95%,并根据分类标签划分为3个风险等级。

中文关键词:乳腺肿瘤 C4.5算法决策树模型构建

Study on the Construction of a Decision-making Model of the Pre-clinical Q&A System for Breast Tumor

Abstract:Purpose/Significance To predict the disease risk of potential or existing breast tumor patients by using a decision tree classification model to simulate the expert consultation idea.Method/Process A C4.5 classical classification algorithm and a pessimistic pruning method are used to predict the outcome of patient pre-consultation for case data collected from the study.Result/Conclusion A C4.5 decision tree with 76 leaf nodes and “whether postoperative radiotherapy or chemotherapy ends in the hospital” as the root node is generated with 95% prediction accuracy and classified into 3 risk levels according to the classification labels.

keywords:breast tumor C4.5 algorithm decision tree model construction

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