Key points are not available for this paper at this time.
BACKGROUND: Artificial intelligence (AI) systems hold great promise in improving medical care and health problems. AIM: We aimed to evaluate the answers by asking the most frequently asked questions to ChatGPT for the prediction and treatment of fever, which is a major problem in children. METHODS: The 50 questions most frequently asked about fever in children were determined, and we asked them to ChatGPT. We evaluated the responses using the quality and readability scales. RESULTS: While ChatGPT demonstrated good quality in its responses, the readability scale and the Patient Education Material Evaluation Tool (PEMAT) scale used with materials appearing on the site were also found to be successful. Among the scales in which we evaluated ChatGPT responses, a weak positive relationship was found between Gunning Fog (GFOG) and Simple Measure of Gobbledygook (SMOG) scores (r = 0.379) and a significant and positive relationship was found between FGL and SMOG scores (r = 0.899). CONCLUSION: This study sheds light on the quality and readability of information regarding the presentation of AI tools, such as ChatGPT, regarding fever, a common complaint in children. We determined that the answers to the most frequently asked questions about fire were high-quality, reliable, easy to read and understandable.
Özdemir et al. (Tue,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: