مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

video

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

sound

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Version

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

View:

135
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Download:

0
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Cites:

Information Journal Paper

Title

Comparison of Data Mining Algorithms in Prediction of Coronary Artery Diseases Using Yazd Health Study (YaHS) Data

Pages

  6824-6835

Abstract

 Introduction: 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.

Cites

  • No record.
  • References

    Cite

    APA: Copy

    Barzegari, Azam, Noorani, Seyede Fatemah, & MIRZAEI, MASOUD. (2023). Comparison of Data Mining Algorithms in Prediction of Coronary Artery Diseases Using Yazd Health Study (YaHS) Data. JOURNAL OF SHAHID SADOUGHI UNIVERSITY OF MEDICAL SCIENCES, 31(7 ), 6824-6835. SID. https://sid.ir/paper/1087118/en

    Vancouver: Copy

    Barzegari Azam, Noorani Seyede Fatemah, MIRZAEI MASOUD. Comparison of Data Mining Algorithms in Prediction of Coronary Artery Diseases Using Yazd Health Study (YaHS) Data. JOURNAL OF SHAHID SADOUGHI UNIVERSITY OF MEDICAL SCIENCES[Internet]. 2023;31(7 ):6824-6835. Available from: https://sid.ir/paper/1087118/en

    IEEE: Copy

    Azam Barzegari, Seyede Fatemah Noorani, and MASOUD MIRZAEI, “Comparison of Data Mining Algorithms in Prediction of Coronary Artery Diseases Using Yazd Health Study (YaHS) Data,” JOURNAL OF SHAHID SADOUGHI UNIVERSITY OF MEDICAL SCIENCES, vol. 31, no. 7 , pp. 6824–6835, 2023, [Online]. Available: https://sid.ir/paper/1087118/en

    Related Journal Papers

  • No record.
  • Related Seminar Papers

  • No record.
  • Related Plans

  • No record.
  • Recommended Workshops






    Move to top
    telegram sharing button
    whatsapp sharing button
    linkedin sharing button
    twitter sharing button
    email sharing button
    email sharing button
    email sharing button
    sharethis sharing button