مقایسه عملکرد الگوریتمهای داده کاوی در پیش بینی بیماریهای عروق کرونر قلبی با استفاده از داده های مطالعه سلامت مردم یزد (یاس).
Introdu ction: Cardiovascular diseases, including ischemic heart disease (IHD ), are one of the main cause of mortality and morbidity worldwide and are currently one of the top ten causes of death. Ischemic heart disease is a type of heart disease that is caused by narrowing of arteries feeding the...
| Publicado en: | Journal of Shaheed Sadoughi University of Medical Sciences & Health Services Vol. 31; no. 7; pp. 6824 - 6836 |
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| Autores principales: | , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Shahid Sadoughi University of Medical Sciences & Health Services
Oct2023
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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=174189517&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 174189517 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 22285741 EUMX jtl: Journal of Shaheed Sadoughi University of Medical Sciences & Health Services issn: 22285741 maglogo: N pubinfo: dt: Oct2023 vid: 31 iid: 7 pid: 69746 pub: Shahid Sadoughi University of Medical Sciences & Health Services artinfo: ui: 174189517 174189517 174189517 10.18502/ssu.v31i7.13693 174189517 ppf: 6824 ppct: 12 formats: tig: atl: مقایسه عملکرد الگوریتمهای داده کاوی در پیش بینی بیماریهای عروق کرونر قلبی با استفاده از داده های مطالعه سلامت مردم یزد (یاس). aug: au: اعظم برزگری سیده فاطمه نوران مسعود میرزائی affil: معاونت تحقیقات و فناوری دانشگاه علوم پزشکی شهید صدوقی یزد ایران. sug: subj: Myocardial Ischemia Diagnosis Data Mining Algorithms Cardiovascular Risk Factors Early Diagnosis Prediction Models Population Characteristics Risk Assessment Human Adult Middle Age Aged Comparative Studies Chest Pain Blood Glucose Analysis Body Mass Index Sociodemographic Factors Random Forest Descriptive Statistics Validity Myocardial Ischemia Mortality Morbidity Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years ab: Introdu ction: Cardiovascular diseases, including ischemic heart disease (IHD ), are one of the main cause of mortality and morbidity worldwide and are currently one of the top ten causes of death. Ischemic heart disease is a type of heart disease that is caused by narrowing of arteries feeding the heart itself. The present study aimed to use data mining algorithms in screening and early prediction of IHD according to the patient's characteristics and risk factors . Methods: In this research, data of the first phase of Yazd Health Study (YaHS), focusing on 21 characteristics of 10,000 participants aged 20 -70 years such as age, type of chest pain, blood sugar level, body mass index, employment status, etc . which have been collected since 2013 were analyzed. Results: Data analysis was conducted using Random Forest and Naive Bayes algorithms which showed 74.51% accuracy in predicting IHD . Conclusion: The study findings revealed that via applying Random Forest and Naive Bayes algorithms, ischemic heart disease can be predicted with high accuracy. Moreover, early screening and timely treatment in the early stages of disease may reduce mortality and morbidity . pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: Persian refInfo: holdings: @attributes: islocal: N |
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