Sign in Subscribe
Machine learning

Artificial Intelligence in Healthcare: A Diagnostic Support Tool in the Emergency Department

Strategic Insights

— 1 min read

A new study published in the Journal of Surgical Education has assessed the potential of artificial intelligence (AI) as a diagnostic support tool for surgical admissions in the Emergency Department. The research, conducted at Tallaght University Hospital, compared the accuracy of AI-driven diagnoses with those made by on-call surgical trainees. The study found that AI systems, specifically ChatGPT-4o, demonstrated similar diagnostic ability to junior surgical trainees, with an accuracy of 76% and substantial agreement between the AI and trainees' initial diagnosis.

Key Takeaways:

  • The study included 100 patients, with a mean age of 54 years and abdominal pain being the most commonly reported symptom.
  • The accuracy of provisional diagnoses compared to CT-confirmed diagnoses was 76% for the AI system and 74% for the surgical trainees (p = 0.744).
  • Substantial agreement between the AI and trainee's initial diagnosis was observed (k = 0.73).
  • There were no statistically significant differences between AI & surgical trainee in provisional diagnosis (p = 0.754), decisions to bring patients to the operating theatre (p = 0.540) and antibiotic administration (p = 0.122).
  • The overall agreement rates were 85%, 58% & 74% respectively.
  • Commercially-available AI models demonstrate similar diagnostic ability to junior surgical trainees and may serve as a useful decision-support system.
  • The research concluded that AI models could be incorporated into electronic record systems as an adjunct to enhance decision-making.
  • The study has been peer-reviewed and published in the Journal of Surgical Education.

Statistics:

  • 100 patients were included in the study.
  • The mean age of presenting cases was 54 (±20), years.
  • Abdominal pain was the most commonly reported symptom in provisional diagnoses (68%).
  • The accuracy of provisional diagnoses compared to CT-confirmed diagnoses was 76% for the AI system and 74% for the surgical trainees (p = 0.744).
  • Substantial agreement between the AI and trainee's initial diagnosis was observed (k = 0.73).
  • 85%, 58% & 74% overall agreement rates respectively.

Sources:

  • NewsRx. New Findings Reported from Tallaght University Hospital Describe Advances in Artificial Intelligence (Assessing Artificial Intelligence as a Diagnostic Support Tool for Surgical Admissions in the Emergency Department). Medical Devices & Surgical Technology Week. September 21, 2025; p 1349.
  • Assessing Artificial Intelligence as a Diagnostic Support Tool for Surgical Admissions in the Emergency Department. Journal of Surgical Education, 2025;82(10):103676.

Read more