Machine‐learning–based early prediction of end‐stage renal disease in patients with diabetic kidney disease using clinical trials data

Evaluating risk prediction models for adults with heart failure: A systematic literature review

(2020) Gian Luca Di Tanna et al.   PLoS One

Change in albuminuria as a surrogate endpoint for progression of kidney disease: a meta-analysis of treatment effects in randomised clinical trials

(2019) Hiddo J L Heerspink et al.   Lancet Diabetes & Endocrinology

Performance of GFR Slope as a Surrogate Endpoint for Kidney Disease Progression in Clinical Trials: A Statistical Simulation

(2019) Tom Greene et al.   JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY

Predicting the early risk of chronic kidney disease in patients with diabetes using real-world data

(2018) Stefan Ravizza et al.   NATURE MEDICINE

Estimated GFR: time for a critical appraisal

(2018) Esteban Porrini et al.   Nature Reviews Nephrology

Calibration drift in regression and machine learning models for acute kidney injury

(2017) Sharon E Davis et al.   JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION

Development and validation of a risk prediction model for end-stage renal disease in patients with type 2 diabetes

(2017) Cheng-Chieh Lin et al.   Scientific Reports

Prediction and detection models for acute kidney injury in hospitalized older adults

(2016) Rohit J. Kate et al.   BMC Medical Informatics and Decision Making

The distance function effect on k-nearest neighbor classification for medical datasets

(2016) Li-Yu Hu et al.   SpringerPlus

Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications

(2016) Paul Thottakkara et al.   PLoS One

Cardiorenal End Points in a Trial of Aliskiren for Type 2 Diabetes

(2012) Hans-Henrik Parving et al.   NEW ENGLAND JOURNAL OF MEDICINE

A Predictive Model for Progression of Chronic Kidney Disease to Kidney Failure

(2011) Navdeep Tangri   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION