Title

Evaluation of AI tools for triage and risk stratification in emergency medicine

Authors

Nikhil Paul^1,*, Parth Jani², Niyati Pandya³, Amrit Podder⁴, Mukul Singh⁵ & Carlos Andres Chango Rodriguez⁶

Affiliation

¹Department of Emergency Medicine, Kasturba Medical College Mangalore, Manipal Academy of Higher Education, Manipal, India; ²Department of General Medicine, Government Medical College, Bhavnagar, Gujarat, India; ³Department of Anaesthesiology, All India Institute of Medical Sciences, Rajkot, Gujarat, India; ⁴Department of Physiology, Teerthanker Mahaveer Medical College & Research Centre, Teerthanker Mahaveer University, Moradabad, Uttar Pradesh, India; ⁵Department of General Surgery, All India Institute of Medical Sciences, Gorakhpur, Uttar Pradesh, India; ⁶Department of Medicine, Physician Armed Forces Hospital, Quito, Ecuador, South America; *Corresponding author

Email

Nikhil Paul - E-mail: josefnikhilpaul@gmail.com
Parth Jani - E-mail: parthjani13@gmail.com
Niyati Pandya - E-mail: niyatipandya9@gmail.com
Amrit Podder - E-mail: amritpodder0@gmail.com
Mukul Singh - E-mail: singhmukul3911@gmail.com
Carlos Andres Chango Rodriguez - E-mail: carlosachangor@gmail.com

Article Type

Research Article

Date

Received October 1, 2025; Revised October 31, 2025; Accepted October 31, 2025, Published October 31, 2025

Abstract

The effectiveness of AI tools in triage and risk stratification in emergency medicine by comparing outcomes between AI-assisted triage and traditional triage methods is of interest. Hence, a total of 300 patients were enrolled, with 150 in each group, over 14 days. Results showed that the AI-assisted triage group had significantly reduced time to treatment, higher accuracy in triage decisions and more efficient resource allocation. Patient outcomes and length of stay were similar across both groups. Data shows that AI tools can enhance triage efficiency without compromising patient care.

Keywords

Accuracy, AI-assisted triage, emergency medicine, risk stratification, triage

Citation

Paul et al. Bioinformation 21(10): 3804-3808 (2025)

Edited by

Ritik Kashwani

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.