| 基于BP-AsymBoost的医疗诊断模型 |
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| 引用本文： | 张涛,郝晓玲,张玥杰,张明辉.基于BP-AsymBoost的医疗诊断模型[J].系统工程理论与实践,2017,37(6):1654-1664. |
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| 作者姓名： | 张涛 郝晓玲 张玥杰 张明辉 |
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| 作者单位： | 1. 上海财经大学 信息管理与工程学院, 上海 200433;
2. 上海市金融信息技术研究重点实验室, 上海 200433;
3. 复旦大学 计算机科学技术学院, 上海市智能信息处理重点实验室, 上海 200433 |
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| 基金项目： | 国家自然科学基金（71171126，71401096，61572140）；教育部高等学校博士学科点专项科研基金（20130078110001） |
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| 摘 要： | 本文主要研究BP神经网络以及AdaBoost算法在医疗诊断中的应用,在分析标准AdaBoost算法的基础上提出改进的AdaBoost算法,即BP-AsymBoost.针对UCI数据库中的威斯康星乳腺癌数据集设计结合BP网络以及改进后的AdaBoost算法的诊断模型,并且通过多个指标将其与BP模型,遗传算法优化的BP模型,未经改进的BP-AdaBoost模型进行比较,验证BP-AsymBoost模型的有效性.
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| 关 键 词： | 智能辅助诊断 分类模型 AdaBoost算法 BP神经网络 BP-AsymBoost模型 |
| 收稿时间： | 2015-10-20 |
A medical diagnosis model based on BP-AsymBoost algorithm |
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| ZHANG Tao,HAO Xiaoling,ZHANG Yuejie,ZHANG Minghui.A medical diagnosis model based on BP-AsymBoost algorithm[J].Systems Engineering —Theory & Practice,2017,37(6):1654-1664. |
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| Authors: | ZHANG Tao HAO Xiaoling ZHANG Yuejie ZHANG Minghui |
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| Institution: | 1. School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai 200433, China;
2. Shanghai Key Laboratory of Financial Information Technology, Shanghai 200433, China;
3. School of Computer Science, Fudan University, Shanghai Key Laboratory of Intelligent Information Processing, Shanghai 200433, China |
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| Abstract: | This paper mainly researches the BP application of neural network and AdaBoost algorithmin medical diagnosis. A novel improved AdaBoost algorithm, BP-AsymBoost, is proposed based on the analysis of the standard AdaBoost algorithm. Based on the datasets from the Wisconsin breast cancer data in UCI database, the diagnosis model is designed combining with the AdaBoost algorithm and the improved BP network. Through the comparsion with the basic BP model, the BP model with genetic algorithm optimization, as well as the BP-AdaBoost model on a number of indicators, the validity of our improved BP-AdaBoost model can be effectively verifed. |
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| Keywords: | computer-aided-dignosis classification model AdaBoost algorithm BP network BP-AsymBoost model |
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