Evaluating the Success Rate of the Online Chat-based Artificial Intelligence Program ChatGPT in Answering Basic Questions Related to Thyroid Cancer

Objective: ChatGPT, an advanced conversational bot based on artificial intelligence (AI) and a large language model (LLM), is designed to understand and generate responses to inputs.This study aims to assess the accuracy of responses provided by ChatGPT to questions that might be asked by patients concerning thyroid cancer.Methods: A total of 27 questions in Turkish, relevant to thyroid cancer and likely to be asked by non-healthcare professionals, were prepared under four categories (general information, diagnosis, treatment, follow-up).These questions were posed to the free public version of ChatGPT, version 3.5.Three experts in endocrine surgery (A.C.D., S. T., .M.) were asked to evaluate the responses.The answers were classified into three categories: appropriate, inappropriate, and insufficient/incomplete. Results:Upon evaluating the responses given by ChatGPT to the prepared questions across the four categories, 9 responses (33.3%) were considered "appropriate" by two of the three experts and "insufficient/incomplete" by one expert.Six responses (22.2%) were deemed "appropriate" by two experts and "inappropriate" by one.Overall, a total of 16 responses (59.25%) were considered "appropriate" by at least two experts. Conclusion:At this stage, AI-based conversational programs like ChatGPT are not seen as capable of replacing a specialist from whom patients receive medical advice.

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Publication Details

Journal
The Anatolian Journal of General Medical Research
Published
2025-04-29
DOI
https://doi.org/10.4274/anatoljmed.2025.02886
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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article

Evaluating the Success Rate of the Online Chat-based Artificial Intelligence Program ChatGPT in Answering Basic Questions Related to Thyroid Cancer

Yiğit Türk, Özer Makay, Gökhan İçöz, Bahadır Emre Baki et al.
The Anatolian Journal of General Medical Research
Artificial Intelligence in Healthcare and Education
article

Evaluating the Success Rate of the Online Chat-based Artificial Intelligence Program ChatGPT in Answering Basic Questions Related to Thyroid Cancer

Yiğit Türk, Özer Makay, Gökhan İçöz, Bahadır Emre Baki, Serkan Teksöz, Murat Özdemir, Ahmet Cem Dural
article en

Abstract

Objective: ChatGPT, an advanced conversational bot based on artificial intelligence (AI) and a large language model (LLM), is designed to understand and generate responses to inputs.This study aims to assess the accuracy of responses provided by ChatGPT to questions that might be asked by patients concerning thyroid cancer.Methods: A total of 27 questions in Turkish, relevant to thyroid cancer and likely to be asked by non-healthcare professionals, were prepared under four categories (general information, diagnosis, treatment, follow-up).These questions were posed to the free public version of ChatGPT, version 3.5.Three experts in endocrine surgery (A.C.D., S. T., .M.) were asked to evaluate the responses.The answers were classified into three categories: appropriate, inappropriate, and insufficient/incomplete. Results:Upon evaluating the responses given by ChatGPT to the prepared questions across the four categories, 9 responses (33.3%) were considered "appropriate" by two of the three experts and "insufficient/incomplete" by one expert.Six responses (22.2%) were deemed "appropriate" by two experts and "inappropriate" by one.Overall, a total of 16 responses (59.25%) were considered "appropriate" by at least two experts. Conclusion:At this stage, AI-based conversational programs like ChatGPT are not seen as capable of replacing a specialist from whom patients receive medical advice.

The Anatolian Journal of General Medical Research
Openalex Percentile: Top 94%
Artificial Intelligence in Healthcare and Education
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Evaluating the Success Rate of the Online Chat-based Artificial Intelligence Program ChatGPT in Answering Basic Questions Related to Thyroid Cancer — Yiğit Türk, Özer Makay, et al. · The Anatolian Journal of General Medical Research (2025) | TGRS Research Map | TGRS