An academic evaluation of ChatGpt’s ability and accuracy in creating patient education resources for rare cardiovascular diseases
Abstract Generative Pre-trained Transformer (ChatGPT) is a web-based artificial intelligence assistant with the potential to provide information, answer questions, and make recommendations on various topics. Rare cardiovascular diseases (rCVD) are among the health problems that require specialized k...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-11567-w |
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| Summary: | Abstract Generative Pre-trained Transformer (ChatGPT) is a web-based artificial intelligence assistant with the potential to provide information, answer questions, and make recommendations on various topics. Rare cardiovascular diseases (rCVD) are among the health problems that require specialized knowledge and attention, and web databases provide relatively limited information. In this study, we investigated the accuracy and reliability of ChatGPT’s answers to patients’ possible questions about rCVD. ChatGPT was asked forty questions about rCVD. Based on current guidelines and information, academicians who are experts in their fields evaluated ChatGPT’s answers to these questions. The success of ChatGPT, which has been repeatedly evaluated in classical diseases, was lower in rCVD. The responses to various questions exhibited significant similarity, with some answers including redundant information. In addition, ChatGPT did not give the desired answers to some questions. However, although some answers were longer than necessary, there was very little incorrect information in the answers. Although ChatGPT is competent in obtaining information about rCVD, physicians should clarify the answers given by ChatGPT to patients. Therefore, ChatGPT should be used as an auxiliary information acquisition tool rather than as a primary resource for patients with rCVD. |
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| ISSN: | 2045-2322 |