Year: 2026
Type: article
Abstract: This article evaluates the potential of artificial intelligence (AI) as a decision-support tool in the selection process for the “Neurotrauma Institutional Award” by the Neurotrauma Society of India, aiming to reduce subjectivity and enhance transparency. Eight anonymized institutional applications were submitted to ChatGPT (August 2024). Sequential prompts were used to generate summaries, assign scores, provide rationales, and deliver detailed justifications across domains including infrastructure, prehospital systems, clinical volume, research/training, and governance. Centers were scored out of 100, and heatmaps were created to visualize comparative performance. Scores were analyzed descriptively, ranging from 60 to 92. Comparative rankings were generated, and discrepancies between AI-based scoring and executive committee voting outcomes were examined. Center C achieved the highest score (92/100), demonstrating strengths in emergency systems, structured triage, integrated trauma registry, simulation culture, and community outreach. The AI-based ranking differed from the executive committee's choice, which had awarded joint winners ranked third and sixth by AI. This highlighted subjectivity in manual selection. AI integration into award selection processes can harmonize heterogeneous data, benchmark institutional performance, and enhance fairness through transparency, consistency, and reproducibility. While AI cannot replace expert judgment, a hybrid AI–expert model is proposed to balance objectivity with domain expertise in future award evaluations.
Source: Indian Journal of Neurosurgery
Author: Dhaval Shukla
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7169560485