• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

使用模糊认知图结合遗传算法的诊断支持

Diagnosis support using Fuzzy Cognitive Maps combined with Genetic Algorithms.

作者信息

Georgopoulos Voula C, Stylios Chrysotomos D

机构信息

Department of Speech and Language Therapy, Technological Educational Institute of Patras, Koukouli 26334, Patras, Greece.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:6226-9. doi: 10.1109/IEMBS.2009.5334647.

DOI:10.1109/IEMBS.2009.5334647
PMID:19965085
Abstract

A new hybrid modeling methodology to support medical diagnosis decisions is developed here. It extends previous work on Competitive Fuzzy Cognitive Maps for Medical Diagnosis Support Systems by complementing them with Genetic Algorithms Methods for concept interaction. The synergy of these methodologies is accomplished by a new proposed algorithm that leads to more dependable Advanced Medical Diagnosis Support Systems that are suitable to handle situations where the decisions are not clearly distinct. The technique developed here is applied successfully to model and test a differential diagnosis problem from the speech pathology area for the diagnosis of language impairments.

摘要

本文开发了一种新的混合建模方法来支持医学诊断决策。它通过用遗传算法方法进行概念交互来补充先前关于医学诊断支持系统的竞争模糊认知地图的工作。这些方法的协同作用是通过一种新提出的算法实现的,该算法可导致更可靠的高级医学诊断支持系统,适用于处理决策不明确的情况。这里开发的技术已成功应用于对言语病理学领域中语言障碍诊断的鉴别诊断问题进行建模和测试。

相似文献

1
Diagnosis support using Fuzzy Cognitive Maps combined with Genetic Algorithms.使用模糊认知图结合遗传算法的诊断支持
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:6226-9. doi: 10.1109/IEMBS.2009.5334647.
2
A hybrid neural network system for pattern classification tasks with missing features.一种用于处理具有缺失特征的模式分类任务的混合神经网络系统。
IEEE Trans Pattern Anal Mach Intell. 2005 Apr;27(4):648-53. doi: 10.1109/TPAMI.2005.64.
3
A review of fuzzy cognitive maps in medicine: Taxonomy, methods, and applications.医学中的模糊认知图综述:分类、方法与应用
Comput Methods Programs Biomed. 2017 Apr;142:129-145. doi: 10.1016/j.cmpb.2017.02.021. Epub 2017 Feb 22.
4
Computational cognitive modeling for the diagnosis of Specific Language Impairment.用于特定语言障碍诊断的计算认知建模
Stud Health Technol Inform. 2013;186:88-92.
5
Clinical diagnosis support system based on case based fuzzy cognitive maps and semantic web.基于案例的模糊认知图和语义网的临床诊断支持系统
Stud Health Technol Inform. 2012;180:295-9.
6
Fuzzy Naive Bayesian for constructing regulated network with weights.用于构建带权重的调控网络的模糊朴素贝叶斯方法。
Biomed Mater Eng. 2015;26 Suppl 1:S1757-62. doi: 10.3233/BME-151476.
7
Generating fuzzy rules for constructing interpretable classifier of diabetes disease.生成用于构建糖尿病疾病可解释分类器的模糊规则。
Australas Phys Eng Sci Med. 2012 Sep;35(3):257-70. doi: 10.1007/s13246-012-0155-z. Epub 2012 Aug 16.
8
Automated diagnosis of coronary artery disease based on data mining and fuzzy modeling.基于数据挖掘和模糊建模的冠状动脉疾病自动诊断
IEEE Trans Inf Technol Biomed. 2008 Jul;12(4):447-58. doi: 10.1109/TITB.2007.907985.
9
A comparative study of fuzzy classification methods on breast cancer data.乳腺癌数据的模糊分类方法比较研究
Australas Phys Eng Sci Med. 2004 Dec;27(4):213-8. doi: 10.1007/BF03178651.
10
Biotechnical measurement and software system for the prediction and diagnosis of osteochondrosis of the lumbar region with the use of fuzzy logic rules.利用模糊逻辑规则预测和诊断腰椎骨软骨病的生物技术测量与软件系统
Biomed Tech (Berl). 2013 Feb;58(1):51-5. doi: 10.1515/bmt-2012-0081.

引用本文的文献

1
Fuzzy Cognitive Map Applications in Medicine over the Last Two Decades: A Review Study.过去二十年中模糊认知图在医学中的应用:一项综述研究。
Bioengineering (Basel). 2024 Jan 30;11(2):139. doi: 10.3390/bioengineering11020139.
2
Modeling paradigms for medical diagnostic decision support: a survey and future directions.医学诊断决策支持的建模范例:调查与未来方向。
J Med Syst. 2012 Oct;36(5):3029-49. doi: 10.1007/s10916-011-9780-4. Epub 2011 Oct 1.