ArticleSkin health and disease2026
Patient perceptions of artificial intelligence integration in dermatology: a cross-sectional study of trust, comfort and equity across multiple care modalities.
Article in Skin health and disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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Who cites it
2 citing papers in PubMed.
- Artificial Intelligence in Dermatology Among Saudi Adults: Cross-Sectional Survey Study.Healthcare (Basel, Switzerland) · 2026Article
- The double-edged sword of generative AI in dermatology: a multi-component cross-sectional study on physician burnout, patient satisfaction, and communication quality.Frontiers in medicine · 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
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial intelligence (AI) and telemedicine are rapidly changing the way dermatological care is delivered. As these tools are increasingly used in tandem, understanding how patients perceive the integration of AI across different care settings is important for responsible implementation. Objectives: To assess patient perceptions of AI in dermatology across five care modalities and examine how demographic factors influence acceptance. Methods: A cross-sectional survey was conducted among 130 adults at a US academic dermatology clinic between December 2024 and April 2025. Participants rated trust, comfort, perceived quality, privacy and confidence in equitable performance across three AI-involved modalities: standalone AI apps, AI-assisted in-person visits and AI-assisted telemedicine visits. Differences in perception outcomes across the three care modalities were analysed using repeated measures Anova. Logistic and linear regressions analysed predictors of acceptance, including age, race, skin tone, socioeconomic status, rurality and technology experience. Results: Patients strongly preferred dermatologist-involved care over standalone AI, with 73.8% trusting dermatologist-guided AI and only 1.5% trusting AI apps alone. Comfort and perceptions of equal performance across skin tones were significantly higher for telemedicine and AI-assisted visits compared with AI apps ( Conclusions: Patients strongly prefer AI as clinical support systems rather than autonomous decision-makers, especially for high-stakes and sensitive concerns. Differences in acceptance by race and skin tone point to the need for better representation in datasets and clearer communication about how these tools perform. Moving forward, development and implementation should emphasize clinician and patient involvement, fairness and patient choice to ensure AI is integrated into dermatology in a way that earns patient trust.
Identifiers
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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.