Rayman Control Panel (4.0.0 and above)

Containerized workflow for analysis of human diabetic kidney disease by snRNA-seq and snATAC-seq

A Python library for kidney failure risk estimation using Tangri's KFRE model

🏥 AI-powered system for Chronic Kidney Disease staging and treatment. Combines a stacking ensemble (CatBoost, XGBoost, LightGBM) with clinical rules to achieve 96.8% accuracy. Includes SHAP explainability, a Streamlit web app, PDF reports, and expert-aligned treatment guidance. Built for clinicians, researchers, and ML developers in healthcare AI.

Medical Utils

Towards a CKD (Chronic Kidney Disease) dataset.

Ckd with React is easy

Containerized workflow for single cell detection of loss of Y chromosome and other mosaic chromosomal alterations in chronic kidney disease

Predicting the hyper-local prevalence of chronic kidney disease with stochastic gradient boosting

Evaluating racial and/or ethnic disparities in the timeliness of nephrology care amongst patients with newly diagnosed CKD. This work will look at time to nephrology follow up once patients are diagnosed with CKD Stage 3 and CKD Stage 4.

Statistical code to replicate the analyses in "The Presence and Impact of Multimorbidity Clusters on Adverse Outcome Across the Spectrum of Kidney Function".

Chronic kidney disease (CKD) is a long-term disorder which causes the kidneys to not function as well as they should.Our goal is to predict whether a subject has the chance of getting chronic kidney disease from a given set of data using machine learning.