Contrasting rule and machine learning based digital self triage systems in the USA

Bilal A Naved; Yuan Luo

doi:10.1038/s41746-024-01367-3

Contrasting rule and machine learning based digital self triage systems in the USA

NPJ Digit Med. 2024 Dec 27;7(1):381. doi: 10.1038/s41746-024-01367-3.

Authors

Bilal A Naved^{1

2}, Yuan Luo³

Affiliations

¹ Department of Biomedical Engineering, Northwestern University McCormick School of Engineering, Chicago, IL, USA.
² Department of Preventative Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
³ Department of Preventative Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA. [email protected].

PMID: 39725711
DOI: 10.1038/s41746-024-01367-3

Abstract

Patient smart access and self-triage systems have been in development for decades. As of now, no LLM for processing self-reported patient data has been published by health systems. Many expert systems and computational models have been released to millions. This review is the first to summarize progress in the field including an analysis of the exact self-triage solutions available on the websites of 647 health systems in the USA.

Publication types

Review

Abstract

Publication types

Grants and funding