作者
Jeel Talaviya, Dhruv Trivedi, Ronish Ramani, Anjali Diwan, Rajesh Mahadeva, Rajesh Mahadeva
发表日期
2024/5/21
研讨会论文
2023 IEEE Technology & Engineering Management Conference - Asia Pacific (TEMSCON-ASPAC)
页码范围
10.1109/TEMSCON-ASPAC59527.2023.10531380
简介
Heart disease remains one of the leading causes of death worldwide, underscoring the critical need for accurate and timely prediction models. The outcome of cardiac disease is one area where machine learning algorithms have shown substantial potential. A rapidly advancing area of research is focused on using machine learning for heart disease prediction. Recent studies have extensively explored machine learning methods to anticipate heart disease in patients. This research aims to develop precise prediction models that can identify individuals at high risk of developing heart disease. These models consider various characteristics such as age, gender, medical history, and lifestyle choices to calculate the likelihood of heart disease. Notably, the accuracy of these machine learning models often surpasses that of traditional methods used for predicting cardiac disease. Integrating machine learning algorithms …
学术搜索中的文章
J Talaviya, D Trivedi, R Ramani, A Diwan, R Mahadeva - 2023 IEEE Technology & Engineering Management …, 2023