Evidence map›Paper›PMID 40504405›Full record

ArticleInternational ophthalmology2025

Artificial intelligence in patient care: evaluating artificial intelligence's accuracy and accessibility in addressing blepharoplasty concerns.

Olivia Ayad, Arsany Yassa, Aman M Patel, Ved A Vengsarkar, Solina Ayad, Silvana Ayad, Mina Mikhael

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Article in International ophthalmology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Olivia AyadArclivia. A Platform for Innovation & Research in AI Integration, NJ, USA.
Arsany YassaDivision of Plastic Surgery, University of Missouri School of Medicine, One Hospital Drive, Columbia, MO, 65212, USA. arsanyyassamd@gmail.com.
Aman M PatelRutgers New Jersey Medical School, Newark, NJ, USA.
Ved A VengsarkarRutgers New Jersey Medical School, Newark, NJ, USA.
Solina AyadArclivia. A Platform for Innovation & Research in AI Integration, NJ, USA.
Silvana AyadArclivia. A Platform for Innovation & Research in AI Integration, NJ, USA.
Mina MikhaelWilmer Eye Institute at Johns Hopkins Hospital, Baltimore, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeArtificial Intelligence (AI) is rapidly advancing and profoundly influencing healthcare, offering the potential to revolutionize access to medical information. As medical misinformation proliferates and online searches for health-related advice increase, there is an escalating need for dependable patient information. This study evaluates the effectiveness of an AI chatbot in delivering information for blepharoplasty candidates. MATERIALS AND

methodsNumerous frequently asked questions on blepharoplasty sourced from the ASPS website were asked to ChatGPT. The responses were then rigorously cross-referenced with relevant scholarly literature and meticulously reviewed by the research team to determine their accuracy. Additionally, the questions were classified into three categories, and the responses were evaluated using Flesch-Kincaid readability metrics, along with ANOVA and trend analysis tests.

resultsDespite minor variations, ChatGPT's responses to blepharoplasty FAQs largely aligned with current literature. Overall readability analysis showed a Flesch Reading Ease score of 31.48, indicating high school complexity with a Flesch-Kincaid Grade Level at 10.92, and 20.97% use of passive voice. The ANOVA results showed that there were no significant differences in readability between the categories (p-values: Flesch Reading Ease = 0.816, Flesch-Kincaid = 0.616, Passive Sentences = 0.115). Trend analysis also showed that the level of response complexity stayed the same across the questions.

conclusionChatGPT is an evolving tool that holds potential for patients in accessing and comprehending medical information. While it can offer accurate insights, it's important to recognize that its answers might not consistently reach complete accuracy or be suitable for patients with varying educational levels.

Indexed as

Artificial IntelligenceBlepharoplastyPatient Education as TopicComprehensionHumansArtificial intelligenceASPSBlepharoplastyDatabaseKnowledge baseMedical information systems

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.