ArticleCureus2024
Evaluating Artificial Intelligence (AI)-Generated Patient Education Guides on Epilepsy: A Cross-Sectional Study of ChatGPT and Google Gemini.
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Comparison of the readability of ChatGPT and Bard in medical communication: a meta-analysis.BMC medical informatics and decision making · 2025Pooled it
- Evaluation of the performance of four different large language models (ChatGPT, DeepSeek, Copilot, and Gemini) in answering oral, and maxillofacial radiology questions: pilot study.BMC oral health · 2026Article
- Assessing the Suitability of ChatGPT and DeepSeek AI for Patient Education on Common Rheumatological Disorders.Cureus · 2025Article
- Quality evaluation of AI-generated diabetes-related health education texts from different generative models.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction Epilepsy is a chronic disorder that requires patient education for management and to avoid triggers and complications. This study aims to evaluate and compare the effectiveness of two artificial intelligence (AI) tools, ChatGPT (version 3.5, OpenAI, Inc., San Francisco, United States) and Google Gemini (version 1.5, Google LLC, Mountain View, California, United States), in generating patient education guides for epilepsy disorders. Methodology A patient education guide was generated on ChatGPT and Google Gemini. The study analyzed the sentence count, readability, and ease of understanding using the Flesch-Kincaid calculator, examined similarity using the QuillBot plagiarism tool, and assessed reliability using a modified DISCERN score. Statistical analysis included an unpaired T-test where a P-value <0.05 is considered significant. Results There was no statistically significant difference between ChatGPT and Google Gemini in terms of word count (p=0.75), sentence count (p=0.96), average words per sentence (p=0.66), grade level (p=0.67), similarity% (p=0.57), and reliability scores (p=0.42). Ease scores generated by ChatGPT and Google Gemini were 38.6 and 43.6 for generalized tonic-clonic seizures (GTCS), 18.7 and 45.5 for myoclonic seizures, and 22.4 and 55.8 for status epilepticus, respectively, showing Google Gemini generated responses notably better (p=0.0493). The average syllables per word (p=0.035) were appreciably lower for Google Gemini-generated responses, with 1.8 for GTCS and myoclonic, 1.7 for status epilepticus against 1.9 for GTCS, 2 for myoclonic, and 2.1 for status epilepticus for ChatGPT responses. Conclusions A significant difference was seen in only two parameters. Further improvement in AI tools is necessary to provide effective guides.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.