Liver Cysts and Artificial Intelligence: Is AI Really a Patient-Friendly Support?

Background: With the advancement of AI-powered online tools, patients are increasingly turning to AI for guidance on healthcare-related issues. Methods: Acting as patients, we posed eight direct questions concerning a common clinical condition—liver cysts—to four AI chatbots: ChatGPT, Perplexity, Copilot, and Gemini. The responses were collected and compared both among the chatbots and with the current literature, including the most recent guidelines. Results: Overall, the responses from the four chatbots were generally consistent with the literature, with only a few inaccuracies noted. For questions addressing “grey areas” in clinical research, all chatbots provided generalized answers. ChatGPT, Copilot, and Gemini highlighted the lack of conclusive evidence in the literature, while Perplexity offered speculative correlations not supported by data. Importantly, all chatbots recommended consulting a healthcare professional. While Perplexity, Copilot, and Gemini included references in their responses, not all cited sources were academic or of medium/high evidence quality. An analysis of Flesch Readability Ease Scores and Estimated Reading Grade Levels indicated that ChatGPT and Gemini provided the most readable and comprehensible responses. Conclusions: The integration of chatbots into real-world healthcare scenarios requires thorough testing to prevent potentially serious consequences from misuse. While undeniably innovative, this technology presents significant risks if implemented improperly.

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Publication Details

Journal
Surgeries
Published
2025-08-29
DOI
https://doi.org/10.3390/surgeries6030073
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Liver Cysts and Artificial Intelligence: Is AI Really a Patient-Friendly Support?

Chiara D’Alterio, Immacolata Iannone, Matteo De Pastena, Alessandro Coppola et al.
Surgeries
Artificial Intelligence in Healthcare and Education
article

Liver Cysts and Artificial Intelligence: Is AI Really a Patient-Friendly Support?

Chiara D’Alterio, Immacolata Iannone, Matteo De Pastena, Alessandro Coppola, Cristina De Padua, Enrico Spalice, Maria Lanzone
article en

Abstract

Background: With the advancement of AI-powered online tools, patients are increasingly turning to AI for guidance on healthcare-related issues. Methods: Acting as patients, we posed eight direct questions concerning a common clinical condition—liver cysts—to four AI chatbots: ChatGPT, Perplexity, Copilot, and Gemini. The responses were collected and compared both among the chatbots and with the current literature, including the most recent guidelines. Results: Overall, the responses from the four chatbots were generally consistent with the literature, with only a few inaccuracies noted. For questions addressing “grey areas” in clinical research, all chatbots provided generalized answers. ChatGPT, Copilot, and Gemini highlighted the lack of conclusive evidence in the literature, while Perplexity offered speculative correlations not supported by data. Importantly, all chatbots recommended consulting a healthcare professional. While Perplexity, Copilot, and Gemini included references in their responses, not all cited sources were academic or of medium/high evidence quality. An analysis of Flesch Readability Ease Scores and Estimated Reading Grade Levels indicated that ChatGPT and Gemini provided the most readable and comprehensible responses. Conclusions: The integration of chatbots into real-world healthcare scenarios requires thorough testing to prevent potentially serious consequences from misuse. While undeniably innovative, this technology presents significant risks if implemented improperly.

SurgeriesVol. 6(3)
Pancreas Centre (Canada) (CA), Sapienza University of Rome (IT)
Openalex Percentile: Top 84%
Artificial Intelligence in Healthcare and Education
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Liver Cysts and Artificial Intelligence: Is AI Really a Patient-Friendly Support? — Chiara D’Alterio, Immacolata Iannone, et al. · Surgeries (2025) | TGRS Research Map | TGRS