Through this project, ONC in partnership with National Institutes of Health (NIH) National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), advanced the application of AI/ML in patient-centered outcomes research (PCOR) by generating high quality training datasets for a chronic kidney disease (CKD) use case – predicting mortality within the first 90 days of dialysis.

This project is a full-stack machine learning web app designed to predict Chronic Kidney Disease (CKD) from patient data. Built with Flask, scikit-learn, and a clean front-end, it offers real-time predictions through a user-friendly interface.

Built an algorithm that will predict whether a patient will have CKD based on the features in the dataset

Predictive Model for early indicators of CKD

This project aims to explore clinical and laboratory features associated with chronic kidney disease (CKD) and to identify key predictors that distinguish CKD from non-CKD individuals.

This paper presents a machine learning study for predicting chronic kidney disease (CKD) progression risk using clinical data

This project presents a neural network-based classifier to predict whether a person is at risk of developing chronic kidney disease (CKD).

Variational Autoencoder to predict severity score for CKD patients

A web application designed to predict the likelihood of Chronic Kidney Disease (CKD)

A Data Mining degree project predicting Chronic Kidney Disease (CKD) using machine learning techniques

The CKD Predictor is a web application that uses a Support Vector Machine (SVM) model to assess a patient's risk of Chronic Kidney Disease (CKD). Users input medical data such as specific gravity, albumin, serum creatinine, hemoglobin, packed cell volume, and hypertension status, and the app calculates and displays the likelihood of CKD.

This project seeks to predict whether person has chronic kidney disease (ckd) or no chronic kidney disease (notckd)?

A Machine Learning-based web application for predicting the presence of Chronic Kidney Disease (CKD) based on clinical parameters.

This project focuses on building a machine learning model to predict Chronic Kidney Disease (CKD) using patient clinical and laboratory data. Early detection of CKD can help initiate timely treatment and reduce long-term health complications.

This report explores the development of a predictive model for chronic kidney disease (CKD) using advanced data analysis and machine learning techniques.

This project aims to develop a machine learning model for predicting chronic kidney disease (CKD) using the Fuzzy K-Nearest Neighbors (F-KNN)

This project focuses on predicting Chronic Kidney Disease (CKD) using machine learning algorithms with the primary objective of minimising false negatives. Early and accurate detection of CKD is crucial for timely intervention and treatment, making this project potentially impactful in the medical domain.

Predicting A Disease Based on The Diagnosis of Another Disease Using Machine Learning. Our project is about predicting a disease based on the diagnosis of another disease using machine learning , to help in early diagnosis of disease by supporting the pathologists and doctors in their decision , our idea is to diagnosis of chronic kidney disease (CKD) as well as predicting other diseases, such as Coronary artery disease (CAD). The motivation that drove us to do this project is in order to estimate whether patients with moderate CKD already show signs and symptoms of HF found in its early stages.

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A Flask web app for predicting Chronic Kidney Disease (CKD) using a trained scikit-learn model. Includes data preprocessing (encoding, scaling), real-time predictions, and a user-friendly interface for entering clinical parameters.

Early detection of ckd using CNN and ML ,prediction of future conditions based on the past reports of a patient.

Predicting CKD for observations

Predicting CKD using machine learning

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This model uses machine learning to predict CKD (Chronic Kidney Disease)

Can we predict the progression of ckd using textual features and language models

This is a machine learning model for predict chronicle kidney disease. This model has 99.06 accuracy to predict CKD.

This project predicts whether a patient has Chronic kidney disease(CKD) based on various medical attributes.

A classification program for predicting Chronic Kidney Disease (CKD) for a patient from a given set of attributes.

A requirement from the Hospital, Management asked us to create a predictive model which will predict the Chronic Kidney Disease (CKD) based on the several parameters.