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All Journal International Journal of Informatics and Communication Technology (IJ-ICT)
Akhtar, Shamim
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Computer Science & IT

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Early prediction of myocardial infarction using proposed score tree algorithm Parveen, Nusrat; Pacharaney, Utkarsha; Hegde, Gayatri; Rafique, Mohammad; Firoj Nalband, Sana; Akhtar, Shamim; Devane, Satish
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v15i2.pp813-822

Abstract

Early detection and diagnosis of a diseases will have a big impact on the medical field and help to prevent loss of life. This study begins by gathering information on myocardial infraction patients from hospitals and focuses on earlier diagnostics. In fact, the pre-processed, confirmed data from a qualified doctor is used for this research. Early prediction of myocardial infarction (MI) is proposed by many researchers. They have used Kaggle datasets that is not recent, and they work on post MI. We have proposed early myocardial infraction detection works on unsupervised datasets. To identify myocardial infraction, numerous machines learning supervised algorithms, including decision tree (DT), random forest (RF), are employed in the literature. In this study, we use the score tree algorithm (STA), which operates on an unsupervised dataset, to present a unique early MI prediction method.
Co-Authors Devane, Satish Firoj Nalband, Sana Hegde, Gayatri Pacharaney, Utkarsha Parveen, Nusrat Rafique, Mohammad