Hereditary Disease Prediction Using Machine Learning

This system utilises machine learning methods to forecast hereditary diseases. These conditions also arise in individuals comingfrom families with faulty recessive or dominant genes. These rare diseases rarely impact more than one person per every thousand or million individuals. The goal of this system is to use family history information to estimate the risk that a person may inherit a disease. These machine learning models — decision trees and random forests — are used to create forecasts. Metrics such as accuracy, precision, recall and F1 score are used to gauge how well the algorithms are performing. These outcomes allow us to identify the algorithm that produces the most accurate forecasts. People can utilise this information to develop strategies for preserving their good health. The main diseases addressed by this system include diabetes, cancer, cardiovascular problems, nervous system defects and hair conditions.