Download PDFOpen PDF in browser

Detection of Cardiovascular Diseases Using Machine Learning and Deep Learning

EasyChair Preprint no. 9880

6 pagesDate: March 21, 2023


Cardiovascular diseases also known as heart diseases are the leading cause of death on a global scale. Early detection of cardiac abnormalities can save many lives and even assist physicians in developing an effective treatment plan. An electrocardiogram (ECG), a common and inexpensive way of detecting the electrical activity of the heart, can be used to diagnose cardiovascular diseases. Numerous studies have been conducted on the use of machine learning algorithms to detect heart disease, though the majority of these models do not provide especially high accuracy. This project used the publicly available ECG image dataset of cardiac patients to identify four main cardiac abnormalities: myocardial infarction, history of myocardial infarction, abnormal heartbeat, and normal person classes.

Keyphrases: and Machine Learning, Cardiovascular diseases, deep learning, ECG images, feature extraction

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Pratipal Rai and Shanelle Kalonice Fernandes and Tenzin Choedon and Tseten Tashi Bhutia},
  title = {Detection of Cardiovascular Diseases Using Machine Learning and Deep Learning},
  howpublished = {EasyChair Preprint no. 9880},

  year = {EasyChair, 2023}}
Download PDFOpen PDF in browser