International Journal of Science, Engineering and TechnologyAuthors: Prof. Dr. Fatima Mohsin Inamdar, Tamanna Ragit, Rishika Raj, Nandini Rahane, Satyam Rahane, Satyam Rahane, Shaunak Rahatekar, Raviraj Raibagkar
Abstract: Every 1 in 7 Indians is affected by chronic kidney diseases (CKD), which often is left unnoticed due to negligence of health. This project introduces us with a digital health twin using machine learning which can predict CKD risk early according to the clinical data. A J48 decision tree [10] algorithm is used for classification due to its simple and easy to understand features. The project contains a user-friendly web interface made using Streamlit [9], which allows the users to input the clinical data and receive the required CKD predictions along with 3D [13] models of kidney health stages. With a good focus on awareness, accessibility, and real-world use, this system focuses on supporting early diagnosis and public education and knowledge on CKD.
DOI: https://doi.org/10.5281/zenodo.17826957
