Paper Key : IRJ************630
Author: Shreya Amol Sidnale,Mansi Tejkumar Bhandari,Prasad Sadashiv Mandi,Mayur Chandrakant Chaudhary
Date Published: 02 Dec 2024
Abstract
In our disease prediction project, we aim to create a system that can predict diseases based on symptoms reported by patients. The system uses advanced machine learning techniques to analyze symptom data and generate predictions. By accurately identifying potential diseases early on, the system can help healthcare professionals make informed decisions and provide timely treatment to patients.To achieve this goal, we collect and preprocess a dataset containing symptom information and corresponding disease diagnoses. We then train machine learning models, such as Support Vector Machine (SVM) and Logistic Regression, using this data. These models learn from the patterns in the symptom data and can predict the likelihood of various diseases based on new symptom inputs.The project also focuses on developing a user-friendly interface that allows healthcare professionals to input patient symptoms easily and receive prediction results quickly. This interface enables seamless interaction between users and the prediction system, facilitating efficient disease diagnosis and treatment planning.Overall, our disease prediction project has the potential to revolutionize healthcare by enabling early disease detection and intervention. By leveraging the power of machine learning, we aim to improve patient outcomes and contribute to better healthcare delivery.
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