Heart Disease Prediction Using Machine Learning
DOI:
https://doi.org/10.47392/IRJAEH.2024.0070Keywords:
Feature Selection, Risk Prediction, Heart Disease, Machine LearningAbstract
Over the past few decades, heart-related diseases, or cardiovascular diseases (CVDs) have emerged as the leading cause of death not only in India but worldwide. They are the main cause of many diseases in the world. Machine learning algorithms and techniques have been applied to various clinical trials to automate the analysis of large and complex data. Recently, many scientists have been using AI techniques to support life and experts to detect heart-related diseases in the care industry. Compared to the brain, which is the largest organ in the human body, the heart is the next largest organ. Blood is pumped and sent to all the organs of the body. Cardiovascular disease prediction plays an important role in clinical practice. Informative studies will be useful in anticipating more data that can help predict various diseases and focus on treatment. There is a lot of data about the patients that are seen each month. The stored data can be a source for predicting future disease outbreaks. Some methods of data mining and artificial intelligence are used to predict heart diseases, such as artificial neural networks (ANN), animation, etc. To reduce the number of people who die from heart disease, we need to do it quickly and have a way to detect it. Data mining techniques and artificial intelligence calculations help experts make better cancer predictions and diagnoses. The main goal of this research project is to use AI statistics to predict coronary heart disease in patients.
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Copyright (c) 2024 International Research Journal on Advanced Engineering Hub (IRJAEH)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.