ReviewThe Journal of investigative dermatology2026
Artificial intelligence-enabled precision medicine for inflammatory skin diseases.
Review in The Journal of investigative dermatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Artificial intelligence-based quantification of epidermal proliferation and apoptosis in human skin.JID innovations : skin science from molecules to population health · 2026Article
- Occupational Contact Dermatitis in the Post-COVID Era: From Barrier Dysfunction and Microbiome Dysbiosis to Prevention and Precision Management.Journal of clinical medicine · 2026Review
- Computational discovery of precision therapeutics for hidradenitis suppurativa.bioRxiv : the preprint server for biology · 2026Article
Corrections and comments
- Update of
Authors and funding
6 authors.
Funding
Abstract
Recent advances in artificial intelligence (AI) and multimodal data collection are revolutionizing dermatology. Generative AI and machine-learning approaches offer opportunities to enhance the diagnosis and treatment of autoimmune and inflammatory skin diseases, including atopic dermatitis, psoriasis, hidradenitis suppurativa, vitiligo, alopecia areata, and rheumatic skin disease. This review examines the current landscape of AI applications for inflammatory skin diseases and explores how generative AI and machine-learning methods can advance the field through deep phenotyping, characterization of disease heterogeneity, drug discovery, precision medicine, and delivery of clinical care. We discuss the promises and challenges of these technologies and present a vision for their integration into clinical practice.
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.