Datasets Comparison

This dataset contains clinical triage cases designed to compare expert medical decisions with AI-generated recommendations. Each entry captures the triage system used, expert judgment, and AI output. The Actual and Predicted columns use numerical values representing the expert and AI triage classifications, enabling easier quantitative analysis of performance and agreement across patient groups and acuity levels. The dataset includes the following variables: TRIAGE_CODING: The triage coding system or framework applied in the scenario. EXPERT_SOLUTION: The triage classification provided by a medical expert (ground truth). CHAT_GPT_SOLUTION: The triage classification generated by the AI model. Adult/Pediatric: Indicates whether the case involves an adult or pediatric patient. Actual: Numerical representation of the expert’s triage classification. Predicted: Numerical representation of the AI model’s triage classification. Acuity: Severity level of the case, indicating urgency of care. Potential Applications: Evaluation of AI performance in triage classification Quantitative comparison of expert vs AI decisions Development and benchmarking of clinical decision-support systems Analysis of triage consistency across acuity levels and patient populations

Artificial Intelligence, Emergency Medicine, Mass Casualty, Triage, Clinical Decision Making, AI-Human Interaction

Creative Commons Attribution 4.0 International

This dataset contains clinical triage cases designed to compare expert medical decisions with AI-generated recommendations. Each entry captures the triage system used, expert judgment, and AI output. The Actual and Predicted columns use numerical values representing the expert and AI triage classifications, enabling easier quantitative analysis of performance and agreement across patient groups and acuity levels. The dataset includes the following variables: TRIAGE_CODING: The triage coding system or framework applied in the scenario. EXPERT_SOLUTION: The triage classification provided by a medical expert (ground truth). CHAT_GPT_SOLUTION: The triage classification generated by the AI model. Adult/Pediatric: Indicates whether the case involves an adult or pediatric patient. Actual: Numerical representation of the expert’s triage classification. Predicted: Numerical representation of the AI model’s triage classification. Acuity: Severity level of the case, indicating urgency of care. Potential Applications: Evaluation of AI performance in triage classification Quantitative comparison of expert vs AI decisions Development and benchmarking of clinical decision-support systems Analysis of triage consistency across acuity levels and patient populations

Artificial Intelligence, Emergency Medicine, Mass Casualty, Triage, Clinical Decision Making, AI-Human Interaction

Creative Commons Attribution 4.0 International