English

Prediction of Kidney Function from Biopsy Images Using Convolutional Neural Networks

Machine Learning 2017-02-08 v1 Quantitative Methods

Abstract

A Convolutional Neural Network was used to predict kidney function in patients with chronic kidney disease from high-resolution digital pathology scans of their kidney biopsies. Kidney biopsies were taken from participants of the NEPTUNE study, a longitudinal cohort study whose goal is to set up infrastructure for observing the evolution of 3 forms of idiopathic nephrotic syndrome, including developing predictors for progression of kidney disease. The knowledge of future kidney function is desirable as it can identify high-risk patients and influence treatment decisions, reducing the likelihood of irreversible kidney decline.

Cite

@article{arxiv.1702.01816,
  title  = {Prediction of Kidney Function from Biopsy Images Using Convolutional Neural Networks},
  author = {David Ledbetter and Long Ho and Kevin V Lemley},
  journal= {arXiv preprint arXiv:1702.01816},
  year   = {2017}
}

Comments

11 pages, 7 figures, 1 page of Appendix

R2 v1 2026-06-22T18:10:56.902Z