ArticleJID innovations : skin science from molecules to population health2026
Assessing public interest in artificial intelligence in dermatology: A Google Trends analysis.
Article in JID innovations : skin science from molecules to population health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Perspectives on Artificial Intelligence in Dermatology: An International Cross-Sectional Study.Medicina (Kaunas, Lithuania) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is rapidly transforming dermatology, particularly through diagnostic imaging and enhancing patient management. Despite expanding clinical applications, public engagement with AI in dermatology remains underexplored. This study addresses this gap by analyzing public interest in AI dermatology over the past decade using Google Trends. Search terms were categorized into groups of "AI dermatology," "general AI," "AI nondermatology," "general dermatology," and "general nondermatology." Monthly Search Volume Index values from January 2015 to January 2025 were collected, and linear and exponential regression models quantified temporal trends. Geographic analysis evaluated the frequency of countries appearing in the top five search volumes for each term. Public interest in AI dermatology terms increased markedly after 2022, with growth of 73.6%, 143.6%, and 59.1% in 2022, 2023, and 2024, respectively. AI dermatology terms demonstrated a steeper linear slope (6.212) compared with general AI (6.181) and dermatology terms (1.61), and an exponential growth factor of 0.551. Interest was highest in Singapore, Ireland, Australia, the Philippines, New Zealand, and the United Arab Emirates. These findings indicate a substantial rise in global engagement with AI in dermatology and highlight the importance of integrating public interest considerations into AI tool development, clinical practice, patient safety, and equitable access.
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.