Published on in Vol 9, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31442, first published .
Assessing the Value of Unsupervised Clustering in Predicting Persistent High Health Care Utilizers: Retrospective Analysis of Insurance Claims Data

Assessing the Value of Unsupervised Clustering in Predicting Persistent High Health Care Utilizers: Retrospective Analysis of Insurance Claims Data

Assessing the Value of Unsupervised Clustering in Predicting Persistent High Health Care Utilizers: Retrospective Analysis of Insurance Claims Data

Journals

  1. Cowley H, Robinette M, Matelsky J, Xenes D, Kashyap A, Ibrahim N, Robinson M, Zeger S, Garibaldi B, Gray-Roncal W. Using machine learning on clinical data to identify unexpected patterns in groups of COVID-19 patients. Scientific Reports 2023;13(1) View
  2. Howson S, McShea M, Ramachandran R, Burkom H, Chang H, Weiner J, Kharrazi H. Improving the Prediction of Persistent High Health Care Utilizers: Retrospective Analysis Using Ensemble Methodology. JMIR Medical Informatics 2022;10(3):e33212 View