Symptoms Based Disease Prediction System Using Machine Learning

Abstract

Abstract: The "Symptoms-Based Disease Prediction System using Machine Learning" project is a solution that intends to help users predict their potential diseases based on the symptoms they enter and other general information. This system uses several machine learning algorithms like Decision Tree, KNN, Naïve Bayes, and Random Forest, which are all implemented using the Python programming language. The project uses a dataset collected from hospitals, which allows the system to provide predictions with high accuracy, and ongoing development is in place to improve accuracy even further. The primary objective of this project is to address the challenges that the health industry faces, where people often ignore common symptoms, leading to more severe conditions due to factors such as laziness, time constraints, or reluctance to consult a doctor. Furthermore, this project intends to reduce the workload on doctors and provide a quick and accurate diagnosis using machine learning, thus supporting the health industry