International Journal of Science, Engineering and TechnologyAuthors: Binay P, Anil H, Ankith G, Tanya B, Prof. Arathi H L
Abstract: Machine learning techniques like Logistic Regression, The Support Vector Machine i.e. (SVM) classifiers, The Random Forest classifiers i.e. (RFC), The Decision Tree classifiers i.e. (DTC), and K-Nearest Neighbor (KNN), as well as basic metrics like heart rate, blood pressure, cholesterol, and pulse rate, the goal of this project is to forecast the occurrence of various diseases like diabetes, heart disease, and Parkinson's disease. The most accurate calculation is used to train the dataset, while Python pickling and streamlit are used to record the model behavior. By entering pertinent disease- related information, the initiative seeks to determine the risk factors for the diseases and provide users a prognosis of whether they have the condition or not. This program can assist people in keeping an eye on their health and taking the necessary actions to prolong.
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