Web Application for Diabetes Prediction using Machine Learning Techniques
Year: 2024
Type: article
Abstract: The objective of this project is to predict a person's risk of having diabetes by utilizing Support Vector Machine (SVM) algorithms in an intuitive web application interface. This application attempts to provide accurate and reasonable predictions by using input health parameters (number of pregnancies, blood pressure, glucose level, insulin level, age, skin thickness, diabetes pedigree function, etc.) that users provide via a graphical user interface (GUI). By combining the power of SVM with user-friendly web technology, the project endeavors to enhance accessibility to predictive healthcare tools. The seamless integration of Machine Learning into a web application facilitates a simple and effective method for diabetes prediction, which could aid people in making accurate choices regarding their health. By promoting preventive measures and giving people early awareness, this initiative hopes to support proactive healthcare.
Authors: Bhavya Marupura, Sai Krishna Vaibhav, Narendra V. G., Shivaprasad G.
Institution: Manipal Academy of Higher Education
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4404763351