Research on Application of Data Mining Algorithm in Cardiac Medical Diagnosis System.
Heart disease is a very common high-incidence disease. Due to the wide variety of pathology of heart disease, how to improve the medical diagnosis of heart disease and carry out earlier intervention and treatment is a problem that needs to be solved urgently. The paper adds the decision tree algorit...
| Publicado en: | BioMed Research International pp. 1 - 12 |
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| Autores principales: | , , , , , , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
5/14/2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=156864737&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 156864737 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 5/14/2022 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 156864737 156864737 156864737 10.1155/2022/7262010 156864737 ppf: 1 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Research on Application of Data Mining Algorithm in Cardiac Medical Diagnosis System. aug: au: Peng, Jianyong Zhang, Xinhao Wang, Lina Zhu, Fang Zhou, Nana Zuo, Yansong Zhou, Tao Gao, Yuan affil: Ultrasonography Department, Rizhao International Heart Hospital, Rizhao, 276825, China sug: subj: Data Mining Algorithms Heart Diseases Diagnosis Diagnosis, Computer Assisted Methods Human Technology Decision Trees Neural Networks (Computer) Support Vector Machine Heart Diseases Ultrasonography ab: Heart disease is a very common high-incidence disease. Due to the wide variety of pathology of heart disease, how to improve the medical diagnosis of heart disease and carry out earlier intervention and treatment is a problem that needs to be solved urgently. The paper adds the decision tree algorithm and its comparison and proposes an optimized classification algorithm Co-SVM. Based on the establishment of a heart disease diagnosis classifier based on data mining algorithms, it is aimed at exploring which of these four algorithms is more suitable for heart disease diagnosis problems and optimizing them. A brief description of the cause, influencing factors, and acquired data of heart disease can be seen from the accuracy and scientificity of the data, which further enhances the authenticity and reliability of the clinical diagnosis model of heart disease. At the same time, the ultrasound diagnosis technology of heart disease is introduced, and the important role of ultrasound diagnosis technology in the medical diagnosis of heart disease is discussed. This thesis uses the heart disease clinical data set to establish a heart disease diagnosis classifier based on the decision tree algorithm, neural network algorithm, support vector machine algorithm, and Co-SVM algorithm. Through experimental comparison and analysis, the optimal classification is selected according to the obtained results. The algorithm is Co-SVM algorithm. The experimental results show that the proposed Co-SVM algorithm has a higher accuracy rate than the other three classic algorithms, and the effectiveness of the Co-SVM algorithm is verified by the evaluation results of multiple algorithms. By applying the Co-SVM algorithm in the medical diagnosis system, it is helpful to assist doctors in making more accurate and precise diagnosis of the condition. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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