Work

Role of Artificial Intelligence-Assisted Decision Support Tool for Common Rhythm Disturbances: A ChatGPT Proof-of-Concept Study

Year: 2024

Type: article

Abstract: Background: The objective of this article was to explore the use of ChatGPT as a clinical support tool for common arrhythmias. Methods: This study assessed the feasibility of using ChatGPT as an AI decision-support tool for common rhythm disturbances. The study was conducted using retrospective data collected from electronic medical records (EMRs) of patients with documented rhythm disturbances. The model's performance was evaluated using sensitivity, specificity, positive predictive value, and negative predictive value. Results: A total of 20,000 patients with rhythm disturbances were included in the study. The ChatGPT model demonstrated high diagnostic accuracy in identifying and diagnosing common rhythm disturbances, with a sensitivity of 93%, specificity of 89%, positive predictive value of 91%, and negative predictive value of 92%. The ROC curve analysis showed an area under the curve (AUC) of 0.743, indicating the excellent diagnostic performance of the ChatGPT model. Conclusion: The model's diagnostic performance was comparable to clinical experts, indicating its potential to enhance clinical decision-making and improve patient outcomes. Clinical trial registration: Not applicable.

Source: Journal of Community Hospital Internal Medicine Perspectives

DOI: 10.55729/2000-9666.1402

Authors: Jahanzeb Malik, Muhammad Waqas Afzal, Salaar Sarwar Khan, Muhammad Rizwan Umer, Bushra Fakhar, Amin Mehmoodi

Institution: Shaikh Zayed Medical College and Hospital

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $500