Integrated Disease Forecasting: Leveraging Deep Learning and Machine Learning for Multi-Disease Prediction

Abstract

Abstract—The paper presents how can we predict multiple disease prediction by utilizing machine learning(ML) and deep learning(DL) techniques by analyzing different datasets consisting of various medical parameters our approach integrates ML algorithms such as Logistic regression,KNN,Random forest,support vector machine for initial classification and then sequentially used DL methodology ANN(Artificial Neural Networks) through this extensive experimentation and validation of real world medical datasets, our proposed framework gives the promising outcomes in achieving a remarkable performance of predicting various diseases such as breast cancer, lung cancer, diabetes, monkeypox, parkinson’s. thus offering valuable insights to get early diagnosis. which helps the healthcare professionals to detect and diagnose the disease at preventive stages to improve the patient care. The interface we used for predicting diseases is Streamlit.