Akash Sharma

What factors will a random forest classifier predict as the leading causes of heart disease?

Started Sept. 27, 2024

Abstract or project description

Heart disease is a leading cause of death in the U.S. currently, so finding out what habits cause it is a big part of preventing it. Heart diseases can occur due to blockages of the arteries leading to the heart, which can be caused by various factors like eating habits or smoking. To predict the habits/genetic conditions that can cause heart disease, I used a random forest classifier which is made up of decision trees to help. Decision trees make a series of decisions to classify data and come up with a result. Multiple decision trees, with their outputs averaged, produce the model’s predicted result. The Random Forest classifier predicted heart disease with a __% accuracy and it found that the most important factors that influence heart disease were ______. Once again, heart disease is a leading cause of death in the U.S. and models like these can be useful to the public or healthcare workers to find out whether or not someone has a chance of getting heart disease. I leave it to future computer scientists to develop the prospect of artificial intelligence in heart disease further.