Comparison of ChatGPT, Gemini, and Le Chat with physician interpretations of medical laboratory questions from an online health forum

Author:

Meyer Annika1ORCID,Soleman Ari2,Riese Janik3,Streichert Thomas1ORCID

Affiliation:

1. Institute of Clinical Chemistry, Faculty of Medicine and University Hospital , 27182 University Hospital Cologne , Cologne , Germany

2. Faculty of Medicine and University Hospital , 27182 University Hospital Cologne , Cologne , Germany

3. Institute of Pathology, Faculty of Medicine , RWTH Aachen University , Aachen , Germany

Abstract

Abstract Objectives Laboratory medical reports are often not intuitively comprehensible to non-medical professionals. Given their recent advancements, easier accessibility and remarkable performance on medical licensing exams, patients are therefore likely to turn to artificial intelligence-based chatbots to understand their laboratory results. However, empirical studies assessing the efficacy of these chatbots in responding to real-life patient queries regarding laboratory medicine are scarce. Methods Thus, this investigation included 100 patient inquiries from an online health forum, specifically addressing Complete Blood Count interpretation. The aim was to evaluate the proficiency of three artificial intelligence-based chatbots (ChatGPT, Gemini and Le Chat) against the online responses from certified physicians. Results The findings revealed that the chatbots’ interpretations of laboratory results were inferior to those from online medical professionals. While the chatbots exhibited a higher degree of empathetic communication, they frequently produced erroneous or overly generalized responses to complex patient questions. The appropriateness of chatbot responses ranged from 51 to 64 %, with 22 to 33 % of responses overestimating patient conditions. A notable positive aspect was the chatbots’ consistent inclusion of disclaimers regarding its non-medical nature and recommendations to seek professional medical advice. Conclusions The chatbots’ interpretations of laboratory results from real patient queries highlight a dangerous dichotomy – a perceived trustworthiness potentially obscuring factual inaccuracies. Given the growing inclination towards self-diagnosis using AI platforms, further research and improvement of these chatbots is imperative to increase patients’ awareness and avoid future burdens on the healthcare system.

Publisher

Walter de Gruyter GmbH

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