A Deep Prediction of Chronic Kidney Disease by Employing Machine Learning Method | Python Project

Опубликовано: 17 Май 2026
на канале: JP INFOTECH PROJECTS
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A Deep Prediction of Chronic Kidney Disease by Employing Machine Learning Method | Python IEEE Final Year Project.
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🔗Email: [email protected],
🌐Website: https://www.jpinfotech.org

📌IEEE Base Paper Title: A Deep Prediction of Chronic Kidney Disease by Employing Machine Learning Method.
💡Implementation Code: Python.
🚀Algorithm / Model Used: Artificial Neural Network (ANN).
🌐Web Framework: Flask.
🖥️Frontend: HTML, CSS, JavaScript.
💰Cost (In Indian Rupees): Rs.3000/.

📘Project Abstract:
👉Chronic Kidney Disease is brought on by a kidney issue. Chronic kidney disease (CKD) is a non-communicable illness that affects 10-15% of the world's population and has a considerable impact on morbidity, mortality, and hospital admission rates for patients worldwide. To reduce the effects of the patient's health difficulties, early and accurate detection of the phases of CKD is thought to be essential.
👉This project aims to develop a system for predicting Chronic Kidney Disease (CKD) using machine learning method. Specifically, the proposed system employs an Artificial Neural Network (ANN) to predict CKD. The dataset used for training and testing the models is the Chronic Kidney Disease dataset from the UCI Machine Learning Repository.
👉The proposed system also built a web application using Flask framework where the users can enter the details and predict whether the CKD is there or not, which makes the system easier and accessible to every individual. The study contributes to the field of medical diagnosis and highlights the potential of using machine learning techniques for improving CKD prediction.

📍REFERENCE:
Deepanita Baidya, Umme Umaima, Md Nazrul Islam, F. M. Javed Mehedi Shamrat, Anik Pramanik, Md. Sadekur Rahman, “A Deep Prediction of Chronic Kidney Disease by Employing Machine Learning Method”, 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI), IEEE Conference, 2022.

🏷️tags:
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