An Effective Diabetes Prediction System using Random Forest Algorithm

Abstract

Diabetes is a prevalent metabolic disorderthat affects a significant number of people globally.Timelydetectionandtreatmentofdiabetescanprevent complications and improve health outcomes.Thehealthcareindustryisfacinganincreasingdemand for better patient care and disease predictionsystems.ThisstudyproposesaDiseasePredictionSystem that integrates various features, including anAIChatBot,DiabetesPredictionSystem,Chat andAppointmentBookingSystem,toimprovediseaseprediction accuracy. The Random Forest algorithm isutilizedintheDiabetesPredictionSystem,whichenhancestheoverallaccuracyofthesystem.Withmultipleinputs,thesystembecomesproficientinaccurately classifying diseases and predicting outputs.The system's accuracy was evaluated using a patientinformationdataset,resultinginanoverallaccuracyof90.4%.TheseresultsdemonstratetheDiseasePrediction System's potential to improve healthcareoutcomes by providingtimely and accurate diseaseprediction.Inconclusion,thisstudy'sproposedsystemhasthepotentialtosignificantlybenefithealthcareproviders and the medical field. With its high diseasepredictionaccuracy,efficientdiseaseclassification,anduser-friendlyfeatures,thissystemcanassisthealthcare professionals in making precise diagnoses,providing effective treatments, and enhancing patientoutcomes.