Multiple Disease Prediction using Machine Lea...

Multiple Disease Prediction using Machine Learning: A Review

Author Name : Anuradha Hiwase , Rutuja Deshmukh , Namrata Anjankar, Isha Bisan , Tushar Kumbhare

ABSTRACT This study aims to develop a system using machine learning to predict multiple diseases like diabetes, heart disease, chronic kidney disease, and cancer. It implements various classification algorithms such as K-Nearest Neighbor, Support Vector Machine, Random Forest, Logistic Regression, and Gaussian naive bayesThe accuracy of each algorithm is compared to find the best one for disease prediction. The goal is to create a web application that can forecast these diseases. By analyzing medical data, the system can detect diseases like Malaria, Jaundice, Dengue, and Tuberculosis using linear regression. The goal is to achieve the highest possible accuracy in predicting diseases based on the symptoms provided by the user.For small issues, the users need to go in person to the hospital for check-up that is longer intense. Also handling the telecom entails appointments is kind of agitated. Such a tangle may be solved by Disease prediction application by giving correct steerage relating to healthy living. Over the past decade, the utilization of the particular disease prediction tools alongside the regarding health has been magnified because of a range of diseases and fewer doctor-patient magnitude relation