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Predictive Modelling For Multiple Diseases Using Machine Learning

Author(s) Kailash Yadav
Country India
Abstract This research project, titled " Predictive Modelling for Multiple Diseases Using Machine Learning " aims to predict several diseases, including diabetes, heart disease, lung cancer, Parkinson's disease, and breast cancer. The project employs various machine learning algorithms such as Support Vector Machines (SVM), logistic regression, random forest, and decision trees. For deployment, the models utilize Streamlit Cloud and the Streamlit library, which provide a user-friendly interface for disease prediction. The application interface offers five disease options: diabetes, Parkinson's disease, breast cancer, lung cancer, and heart disease. Users input relevant information for the selected disease, and the application swiftly generates a prediction result, indicating whether the individual may be affected by the condition. This research leverages machine learning techniques to meet the need for accurate disease prediction, facilitating early detection and preventive measures. The intuitive interface provided by the Streamlit library and Streamlit Cloud enhances accessibility and usability, allowing users to easily assess their risk for various diseases. The high accuracy of the different models demonstrates the effectiveness of the machine learning algorithms employed in disease prediction.
Keywords Machine learning, deep learning, datasets, streamlit, heart disease prediction, diabetes detection, lung cancer detection, breast cancer detection.
Field Engineering
Published In Volume 5, Issue 7, July 2024
Published On 2024-07-10
Cite This Predictive Modelling For Multiple Diseases Using Machine Learning - Kailash Yadav - IJLRP Volume 5, Issue 7, July 2024.
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