Evaluation of AI tools for triage and risk stratification in emergency medicine
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.
Authors
- Piyush Jani
- Nikhil Paul (ORCID: https://orcid.org/0000-0001-8520-2565)
- Amrit Podder (ORCID: https://orcid.org/0000-0002-9816-3347)
- Mukul Singh (ORCID: https://orcid.org/0000-0003-3865-7916)
- Niyati Pandya
- C Rodriguez
Institutions
- Manipal Academy of Higher Education (IN)
- Government Medical College Bhavnagar (IN)
- Armed Forces Hospital (SA)
- Teerthanker Mahaveer Medical College & Research Centre (IN)
- All India Institute of Medical Sciences (IN)
Publication Details
- Journal
- Bioinformation
- Published
- 2025-10-31
- DOI
- https://doi.org/10.6026/973206300213804
- Primary Topic
- Emergency and Acute Care Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00