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*Corresponding Author: sardarmirzaahsan@gmail.com
Machine learning and ai are critical to many industries. We are everywhere, from driverless cars to healthcare. In the medical industry, the abundance of patient data presents an opportunity for leveraging machine learning techniques to enhance disease detection and diagnosis. In this project, we present a comprehensive Prediction System capable of detecting multiple diseases simultaneously, addressing the limitations of existing systems that often offer lower accuracy and focus on individual diseases. Our system currently focuses on five major diseases: Heart, Liver, Diabetes, Lung Cancer, and Parkinson's disease, with the potential for expansion to include more diseases in the future. By incorporating various parameters specific to each disease, users can input their data and receive reliable predictions regarding disease presence. The implications of this project are significant, as it enables individuals to monitor their health conditions and take proactive measures, ultimately leading to improved life expectancy. Using the power of machine learning, we aim to contribute to the well-being of countless individuals, providing accurate disease predictions that can potentially save lives.
Supervised Learning, Hypothesis Generation, Exploratory Data Analysis, Feature Engineering, Pre-processing Data, Modelling, Logistic Regression, Predictive System, Support Vector Machine (SVM), κ-Nearest Neighbours Algorithm (KNN), Deployment, Streamlit Cloud