English

Predicting readmission risk from doctors' notes

Machine Learning 2017-12-21 v2

Abstract

We develop a model using deep learning techniques and natural language processing on unstructured text from medical records to predict hospital-wide 3030-day unplanned readmission, with c-statistic .70.70. Our model is constructed to allow physicians to interpret the significant features for prediction.

Cite

@article{arxiv.1711.10663,
  title  = {Predicting readmission risk from doctors' notes},
  author = {Erin Craig and Carlos Arias and David Gillman},
  journal= {arXiv preprint arXiv:1711.10663},
  year   = {2017}
}

Comments

Accepted poster at NIPS 2017 Workshop on Machine Learning for Health (https://ml4health.github.io/2017/)

R2 v1 2026-06-22T23:00:22.563Z