Use of a machine learning model to predict retention in care in an urban HIV clinic-Reference-Cited by-同舟云学术

Use of a machine learning model to predict retention in care in an urban HIV clinic

Published:2023-12-07 Issue:1 Volume:38 Page:125-127
ISSN:0269-9370
Container-title:AIDS
language:en
Short-container-title:

Author:

Schmalzle Sarah A.¹,Maroosis Demetri²,Masur Henry³,Kottilil Shyam¹,Mathur Poonam¹

Affiliation:

1. Institute of Human Virology, University of Maryland School of Medicine, Baltimore

2. Stellar IT Solutions, Inc., Rockville

3. Critical Care Medicine Department, NIH Clinical Center, Bethesda, Maryland, USA.

Abstract

Identifying barriers to retention in care (RIC) is critical to ending the HIV epidemic in the United States. Therefore, we developed a machine learning model (MLM) to identify predictive factors for RIC in an urban HIV clinic. Our MLM yielded a positive predictive value of 84%, higher than previously reported MLMs. We found that MLM can be used to develop interventional strategies to enhance RIC in HIV care.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Infectious Diseases,Immunology,Immunology and Allergy

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