ReviewDigital health
Advances in the study and application of digital technology in the clinical practice of atopic dermatitis.
Review in Digital health. 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
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
2 citing papers in PubMed.
- Investigating the evidence for effective digital skin surveillance methods.Occupational medicine (Oxford, England) · 2026Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Atopic dermatitis (AD) is a complex, chronic inflammatory skin disease that requires individualised and precise diagnostic and treatment strategies. In recent years, digital technologies have opened new avenues for its diagnosis and treatment. This article descriptively reviews the progress of digital technologies in AD from four aspects: diagnosis, treatment, care, and research and development. Artificial intelligence (AI)-assisted analysis of skin lesion images improves diagnostic objectivity, while skin ultrasound quantifies inflammatory indicators. Telemedicine platforms optimise treatment plans by integrating real-time monitoring data, and smart devices enhance skin barrier management. Multi-omics combined with AI-assisted drug design accelerates the development of targeted therapies. Despite challenges such as data privacy and technical standardisation, digital technologies are establishing a closed-loop system of "monitoring-intervention-feedback," driving a paradigm shift in AD diagnosis and treatment. Future efforts should focus on deepening technology integration, interdisciplinary collaboration and real-world data application to achieve full-cycle individualised management.
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.