ChatGPT and Clinical Decision Support: Scope, Application, and Limitations

The Potential Applications and Challenges of ChatGPT in the Medical Field

ChatGPT, an AI-driven conversational large language model (LLM), has garnered significant scholarly attention since its inception, owing to its manifold applications in the realm of medical science. This study primarily examines the merits, limitations, anticipated developments, and practical applications of ChatGPT in clinical practice, healthcare, medical education, and medical research. It underscores the necessity for further research and development to enhance its performance and deployment. Moreover, future research avenues encompass ongoing enhancements and standardization of ChatGPT, mitigating its limitations, and exploring its integration and applicability in translational and personalized medicine. Reflecting the narrative nature of this review, a focused literature search was performed to identify relevant publications on ChatGPT's use in medicine. This process was aimed at gathering a broad spectrum of insights to provide a comprehensive overview of the current state and future prospects of ChatGPT in the medical domain. The objective is to aid healthcare professionals in understanding the groundbreaking advancements associated with the latest artificial intelligence tools, while also acknowledging the opportunities and challenges presented by ChatGPT.

Large Language Models and Healthcare Alliance: Potential and Challenges of Two Representative Use Cases

Large language models (LLMS) emerge as the most promising Natural Language Processing approach for clinical practice acceleration (i.e., diagnosis, prevention and treatment procedures). Similarly, intelligent conversational systems that leverage LLMS have disruptively become the future of therapy in the era of ChatGPT. Accordingly, this research addresses the application of LLMS in healthcare, paying particular attention to two relevant use cases: cognitive decline and depression, more specifically, postpartum depression. In the end, the most promising opportunities they represent (e.g., clinical tasks augmentation, personalized healthcare, etc.) and related concerns (e.g., data privacy and quality, fairness, etc.) are discussed to contribute to the global debate on their integration in the sanitary system.

Reliability and Usefulness of ChatGPT for Inflammatory Bowel Diseases: An Analysis for Patients and Healthcare Professionals

AIM

We aimed to evaluate the performance of Chat Generative Pre-trained Transformer (ChatGPT) within the context of inflammatory bowel disease (IBD), which is expected to become an increasingly significant health issue in the future. In addition, the objective of the study was to assess whether ChatGPT serves as a reliable and useful resource for both patients and healthcare professionals.

METHODS

For this study, 20 specific questions were identified for the two main components of IBD, which are Crohn's disease (CD) and ulcerative colitis (UC). The questions were divided into two sets: one set contained questions directed at healthcare professionals while the second set contained questions directed toward patients. The responses were evaluated with seven-point Likert-type reliability and usefulness scales.

RESULTS

The distribution of the reliability and utility scores was calculated into four groups (two diseases and two question sources) by averaging the mean scores from both raters. The highest scores in both reliability and usefulness were obtained from professional sources (5.00± 1.21 and 5.15±1.08, respectively). The ranking in terms of reliability and usefulness, respectively, was as follows: CD questions (4.70±1.26 and 4.75±1.06) and UC questions (4.40±1.21 and 4.55±1.31). The reliability scores of the answers for the professionals were significantly higher than those for the patients (both raters, p=0.032).  Conclusion: Despite its capacity for reliability and usefulness in the context of IBD, ChatGPT still has some limitations and deficiencies. The correction of ChatGPT's deficiencies and its enhancement by developers with more detailed and up-to-date information could make it a significant source of information for both patients and medical professionals.