Disease Predictor Using Random Forest Classifier
Swatik Paul, Pinku Ranjan, Somesh Kumar, A. Arun Kumar
Abstract
In this paper, a disease prediction system has been designed that takes the symptoms entered by an individual as input and shows the predicted output i.e. the most probable disease to them. Random Forest Classifier algorithm is being used in the backend for prediction purposes. The dataset that is being used consists of 132 symptoms that are linked to 41 diseases. In addition, the system could also suggest precautions and medicines to the user based on their disease. This can minimize the efforts and time invested by the doctors and patients by automatizing the process.
Topics & Concepts
Random forestClassifier (UML)Computer scienceMachine learningArtificial intelligenceDiseaseData miningPattern recognition (psychology)MedicinePathologyArtificial Intelligence in HealthcareImbalanced Data Classification TechniquesData Mining Algorithms and Applications