Evaluation of accuracy, quality, and readability of information on hypothyroidism provided by different artificial intelligence chatbot models
Ting Ruan, Xinran Shao, Yihan Sun, Xingai Ju, Jianchun Cui · 2025
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Description
Ting Ruan and colleagues grade three AI chatbots on thyroid patient questions, in work from 2025. Patients increasingly ask chatbots about underactive thyroid diagnosis, treatment, and long term risks. Answers must match clinic guidelines and stay readable for lay users at home.
Twenty-seven expert written questions went to three leading chatbot models for answers. Two reviewers scored accuracy and quality, while formulas graded reading ease levels. All three bots scored high on accuracy and quality against guideline text. One bot dipped on treatment answers compared with its diagnosis answers, though. Every bot wrote at college reading level, too hard for many patients.
Catalog record
| CREATOR | Ting Ruan, Xinran Shao, Yihan Sun, Xingai Ju, Jianchun Cui |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 52 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |