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Assessment of the Readability of Google Gemini-Generated Versus UpToDate Clinical Contents for Ventricular
Akash Ranganatha1, Veena Ramanathan2, Nikhil Vamsi Chitte3
1Internal Medicine, Jagadguru Jayadeva Murugarajendra (JJM) Medical College, Davanagere, IND.
Insights
Google Gemini content on ventricular tachycardia (VT) shows simpler sentences but more complex words than UpToDate. Expert review is crucial for AI-generated medical information.
Area of Science:
- Medical informatics
- Artificial intelligence in healthcare
- Clinical communication
Background:
- Ventricular tachycardia (VT) is a critical cardiac arrhythmia demanding expert clinical management.
- Artificial intelligence (AI) tools like Google Gemini are emerging for medical content generation.
- UpToDate is a widely recognized expert-authored clinical decision support resource.
Purpose of the Study:
- To objectively compare the readability of AI-generated (Google Gemini) and expert-authored (UpToDate) medical content on VT.
- To utilize standardized readability indices for quantitative analysis.
Main Methods:
- A cross-sectional study analyzed 12 VT management texts (6 Google Gemini, 6 UpToDate).
- Readability assessed using Flesch Reading Ease (FRE), Flesch-Kincaid Grade Level (FKGL), SMOG Index, and Difficult Word Percentage.
- Mann-Whitney U test used for non-normally distributed data; clinical accuracy was not evaluated.
Main Results:
- Google Gemini had a lower median FKGL (13.5) than UpToDate (16.5), indicating simpler sentence structure (p=0.017).
- Google Gemini content had a higher Difficult Word Percentage (32.0%) than UpToDate (28.6%), suggesting greater lexical density (p=0.026).
- No significant differences found in FRE or SMOG Index (p > 0.05).
Conclusions:
- Google Gemini content exhibits syntactic simplicity alongside concentrated technical vocabulary.
- AI-generated medical content presents distinct linguistic patterns compared to expert sources.
- Expert oversight is essential for AI-generated medical content in education and communication to ensure clarity and accuracy.
Abstract:
Introduction Ventricular tachycardia (VT) is a life-threatening arrhythmia requiring complex management. Google Gemini is increasingly used to generate medical content, while UpToDate remains a leading expert-authored clinical reference. This study compared the "readability," not the "clinical accuracy," of VT-related content generated by Google Gemini and UpToDate. Aims This study aims to objectively compare the readability of Google Gemini-generated medical content and UpToDate expert-authored material on VT using standardized readability indices. Methods A cross-sectional study analyzed 12 textual responses on VT management: six from Google Gemini and six from UpToDate. Readability was assessed using the WebFX Readability Test Tool, which calculates Flesch Reading Ease (FRE), Flesch-Kincaid Grade Level (FKGL), Simple Measure of Gobbledygook (SMOG) Index, and Difficult Word Percentage. As the data were non-normally distributed, the Mann-Whitney U test was applied. The analysis was limited to quantitative readability metrics and did not assess clinical accuracy or human comprehension. Results The median FKGL score was 16.5 for UpToDate and 13.5 for Google Gemini (p = 0.017), indicating that UpToDate text required a more advanced reading level. The median Difficult Word Percentage was 32.0% for Google Gemini and 28.6% for UpToDate (p = 0.026), suggesting that Google Gemini content contained a higher proportion of multisyllabic or specialized words. No significant differences were observed in FRE or SMOG Index values (p > 0.05). Conclusion Google Gemini-generated content demonstrated a simpler sentence structure but greater lexical density compared to UpToDate. This highlights a distinct linguistic pattern: syntactic simplicity combined with concentrated technical vocabulary. These findings emphasize the importance of expert review when using Google Gemini-generated material in medical education and communication.
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