ArticleMayo Clinic proceedings. Digital health2024
Skin and Digital-The 2024 Narrative.
Article in Mayo Clinic proceedings. Digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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
7 citing papers in PubMed.
- AI and Digital Tools in Dermatology: Addressing Access and Misinformation.JMIR dermatology · 2026Review
- Preferences of Chinese Dermatologists for Large Language Model Responses in Clinical Psoriasis Scenarios: A Nationwide Cross-Sectional Survey in China.Health care science · 2026Article
- Sustainability in Cosmetic Dermatology: Moving Toward an Ecologically Responsible Future.Dermatology and therapy · 2025Article
- Skin & Digital: The 2024 Startups.JID innovations : skin science from molecules to population health · 2025Article
- Biological Effects ofPlants (Basel, Switzerland) · 2025Review
- Skin & Digital: The 2023 Startups/Innovators.JID innovations : skin science from molecules to population health · 2025Article
- Bridging clinic to home: domestic devices in dermatological diagnostics and treatments.Frontiers in digital health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
24 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The global burden of skin diseases affects over 3 billion individuals, posing important public health challenges worldwide, with profound impacts in both high-income and low-income and middle-income countries. These challenges are exacerbated by widespread disparities in access to dermatologic care and the prevalence of misinformation. This article, derived from the Skin and Digital Summit at the International Master Course on Aging Science critically evaluates how digital technologies such as artificial intelligence, teledermatology, and large language models can bridge these access gaps. It explores practical applications and case studies demonstrating the impact of these technologies in various settings, with a particular focus on adapting solutions to meet the diverse needs of low-income and middle-income countries. In addition, the narrative highlights the ongoing conversation within the dermatologic community about the role of digital advances in health care, emphasizing that this discussion is dynamic and the one that is continuously evolving. Dermatologists play an essential role in this transition, integrating digital tools into mainstream care to complement a patient-centered, culturally sensitive approach. The article advocates for a globally coordinated digital response that not only addresses current disparities in skin health care but also promotes equitable access to digital health resources, making dermatologic care more representative of all skin types and accessible worldwide.
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.