Multiple Disease Prediction System Using ML
DOI:
https://doi.org/10.31033/ijemr.13.3.12Keywords:
Machine Learning, Data Analysis, Supervised Learning, Hypothesis Generation, Exploratory Data Analysis, Data Insights, Feature Engineering, Pre-processing Data, Modelling, Logistic Regression, Predictive System, Support Vector Machine, k-nearest neighbours Algorithm, Deployment, Streamlit CloudAbstract
Machine Learning and Artificial Intelligence have become integral components of numerous industries. From self-driving cars to medical fields, we can find them everywhere. 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. By harnessing 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.
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Copyright (c) 2023 Ahsan Ahmad Beg, Fazla Maqsood, Dr. Sifatullah Siddiqi
This work is licensed under a Creative Commons Attribution 4.0 International License.