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

Bilal A. Naved, Yuan Luo^*

^*Corresponding author for this work

Preventive Medicine

Research output: Contribution to journal › Review article › peer-review

1 Scopus citations

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.

Original language	English (US)
Article number	381
Journal	npj Digital Medicine
Volume	7
Issue number	1
DOIs	https://doi.org/10.1038/s41746-024-01367-3
State	Published - Dec 2024

Funding

This study is supported in part by NIH grants R01LM013337 (YL).

ASJC Scopus subject areas

Medicine (miscellaneous)
Health Informatics
Computer Science Applications
Health Information Management

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10.1038/s41746-024-01367-3

Cite this

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

Abstract

Funding

ASJC Scopus subject areas

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