Using python and libraries such as pandas, sckikit-learn and altair our group was able to build a heart disease detection model using historical data. Utilizing the a dataset from UC Irvine's Machine Learning Repository, we meticulously analyzed data from 303 patients who underwent coronary angiography at the Cleveland Clinic from May 1981 to September 1984. Our approach harnessed the k-nearest neighbors classifier, renowned for its simplicity and accuracy, particularly in medical diagnostics.
All required libraries are listed in the requirements.txt .
pip install -r requirements.txt