Reply to “Comment on ChatGPT failed Taiwan’s Family Medicine Board Exam”

Weng, Tzu-Ling; Chen, Tzeng Ji

doi:10.1097/jcma.0000000000000956

Cited by 4 publications

(2 citation statements)

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“…As a consequence, ChatGPT’s responses may not always be up-to-date or entirely accurate for all scenarios ( 21 ). In a recent publication, Weng et al stated that ChatGPT had failed Taiwan’s Family Medicine Board Exam ( 22 ). The authors hypothesized that possible factors that had contributed to these results included the challenging nature of the specialist exam in family medicine and the limited availability of comprehensive traditional Chinese-language resources for processing medical problems.…”

Section: Discussionmentioning

confidence: 99%

“…The authors hypothesized that possible factors that had contributed to these results included the challenging nature of the specialist exam in family medicine and the limited availability of comprehensive traditional Chinese-language resources for processing medical problems. Despite these challenges, the authors argued that ChatGPT had demonstrated satisfactory performance in handling negatively phrased questions, mutually exclusive questions, and case-scenario questions, thereby suggesting its potential as a valuable learning and exam-preparation tool ( 22 ).…”

Section: Discussionmentioning

confidence: 99%

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ChatGPT’s performance in German OB/GYN exams – paving the way for AI-enhanced medical education and clinical practice

Riedel,

Kaefinger,

Stuehrenberg

et al. 2023

Front. Med.

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BackgroundChat Generative Pre-Trained Transformer (ChatGPT) is an artificial learning and large language model tool developed by OpenAI in 2022. It utilizes deep learning algorithms to process natural language and generate responses, which renders it suitable for conversational interfaces. ChatGPT’s potential to transform medical education and clinical practice is currently being explored, but its capabilities and limitations in this domain remain incompletely investigated. The present study aimed to assess ChatGPT’s performance in medical knowledge competency for problem assessment in obstetrics and gynecology (OB/GYN).MethodsTwo datasets were established for analysis: questions (1) from OB/GYN course exams at a German university hospital and (2) from the German medical state licensing exams. In order to assess ChatGPT’s performance, questions were entered into the chat interface, and responses were documented. A quantitative analysis compared ChatGPT’s accuracy with that of medical students for different levels of difficulty and types of questions. Additionally, a qualitative analysis assessed the quality of ChatGPT’s responses regarding ease of understanding, conciseness, accuracy, completeness, and relevance. Non-obvious insights generated by ChatGPT were evaluated, and a density index of insights was established in order to quantify the tool’s ability to provide students with relevant and concise medical knowledge.ResultsChatGPT demonstrated consistent and comparable performance across both datasets. It provided correct responses at a rate comparable with that of medical students, thereby indicating its ability to handle a diverse spectrum of questions ranging from general knowledge to complex clinical case presentations. The tool’s accuracy was partly affected by question difficulty in the medical state exam dataset. Our qualitative assessment revealed that ChatGPT provided mostly accurate, complete, and relevant answers. ChatGPT additionally provided many non-obvious insights, especially in correctly answered questions, which indicates its potential for enhancing autonomous medical learning.ConclusionChatGPT has promise as a supplementary tool in medical education and clinical practice. Its ability to provide accurate and insightful responses showcases its adaptability to complex clinical scenarios. As AI technologies continue to evolve, ChatGPT and similar tools may contribute to more efficient and personalized learning experiences and assistance for health care providers.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

ChatGPT’s performance in German OB/GYN exams – paving the way for AI-enhanced medical education and clinical practice

Riedel,

Kaefinger,

Stuehrenberg

et al. 2023

Front. Med.

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Beyond human in neurosurgical exams: ChatGPT's success in the Turkish neurosurgical society proficiency board exams

Sahin,

Sozer,

Kuzucu

et al. 2024

Computers in Biology and Medicine

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Exploring ChatGPT in clinical inquiry: a scoping review of characteristics, applications, challenges, and evaluation

Abhari,

Afshari,

Fatehi

et al. 2024

Annals of Medicine &Amp; Surgery

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Introduction: Recent advancements in generative AI, exemplified by ChatGPT, hold promise for healthcare applications such as decision-making support, education, and patient engagement. However, rigorous evaluation is crucial to ensure reliability and safety in clinical contexts. This scoping review explores ChatGPT’s role in clinical inquiry, focusing on its characteristics, applications, challenges, and evaluation. Methods: This review, conducted in 2023, followed PRISMA-ScR guidelines, Supplemental Digital Content 1, http://links.lww.com/MS9/A636. Searches were performed across PubMed, Scopus, IEEE, Web of Science, Cochrane, and Google Scholar using relevant keywords. The review explored ChatGPT’s effectiveness in various medical domains, evaluation methods, target users, and comparisons with other AI models. Data synthesis and analysis incorporated both quantitative and qualitative approaches. Results: Analysis of 41 academic studies highlights ChatGPT’s potential in medical education, patient care, and decision support, though performance varies by medical specialty and linguistic context. GPT-3.5, frequently referenced in 26 studies, demonstrated adaptability across diverse scenarios. Challenges include limited access to official answer keys and inconsistent performance, underscoring the need for ongoing refinement. Evaluation methods, including expert comparisons and statistical analyses, provided significant insights into ChatGPT’s efficacy. The identification of target users, such as medical educators and non-expert clinicians, illustrates its broad applicability. Conclusion: ChatGPT shows significant potential in enhancing clinical practice and medical education. Nevertheless, continuous refinement is essential for its successful integration into healthcare, aiming to improve patient care outcomes and address the evolving needs of the medical community.

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Reply to “Comment on ChatGPT failed Taiwan’s Family Medicine Board Exam”

Cited by 4 publications

References 4 publications

ChatGPT’s performance in German OB/GYN exams – paving the way for AI-enhanced medical education and clinical practice

ChatGPT’s performance in German OB/GYN exams – paving the way for AI-enhanced medical education and clinical practice

Beyond human in neurosurgical exams: ChatGPT's success in the Turkish neurosurgical society proficiency board exams

Exploring ChatGPT in clinical inquiry: a scoping review of characteristics, applications, challenges, and evaluation

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