ArticleJournal of medical systems2018
Design of an Algorithm for Automated, Computer-Guided PASI Measurements by Digital Image Analysis.
Article in Journal of medical systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Mild psoriasis as a suitable model for proof-of-mechanism in a phase 1B setting: Results from a double-blind placebo-controlled trial with guselkumab.British journal of clinical pharmacology · 2025Trial
- Non-invasive clinical and microscopic evaluation of the response to treatment with clobetasol cream vs. calcipotriol/betamethasone dipropionate foam in mild to moderate plaque psoriasis: an investigator-initiated, phase IV, unicentric, open, randomized clinical trial.Journal of the European Academy of Dermatology and Venereology : JEADV · 2021Trial
- Aloesin alleviates imiquimod-induced psoriasis in dermal layers through inhibition of interleukins and NF-κB signaling pathways.Scientific reports · 2025Article
- AI in Aesthetic/Cosmetic Dermatology: Current and Future.Journal of cosmetic dermatology · 2025Review
- Artificial Intelligence: A Snapshot of Its Application in Chronic Inflammatory and Autoimmune Skin Diseases.Life (Basel, Switzerland) · 2024Review
- Patient-physician (dis)agreement on their reports of body surface area affected by psoriasis and its associations with disease burden.Journal of the European Academy of Dermatology and Venereology : JEADV · 2022Article
- Artificial Intelligence in Dermatology Image Analysis: Current Developments and Future Trends.Journal of clinical medicine · 2022Review
- Image-based automated Psoriasis Area Severity Index scoring by Convolutional Neural Networks.Journal of the European Academy of Dermatology and Venereology : JEADV · 2022Article
- Machine Learning Applications in the Evaluation and Management of Psoriasis: A Systematic Review.Journal of psoriasis and psoriatic arthritis · 2020Article
- [Role of artificial intelligence in assessing the extent and progression of dermatoses].Der Hautarzt; Zeitschrift fur Dermatologie, Venerologie, und verwandte Gebiete · 2020Review
- Blueprint for mechanistic, data-rich early phase clinical pharmacology studies in dermatology.British journal of clinical pharmacology · 2020Article
- [New optical examination procedures for the diagnosis of skin diseases].Der Hautarzt; Zeitschrift fur Dermatologie, Venerologie, und verwandte Gebiete · 2020Review
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
The Psoriasis Area and Severity Index (PASI) is the most accepted method for psoriasis severity scoring. However, a prominent level of subjectivity and a low intra- and inter-rater reproducibility was reported. Therefore, an accurate and reproducible measure of psoriasis severity is needed, especially in the setting of registration studies for systemic anti-psoriatic drugs. Herein we describe a robust, user-friendly, computer-guided technology that allows for automated PASI measurements after total body imaging and digital image analysis. For this purpose, a novel image processing software for PASI calculations was developed, which was combined with a commercially available, automated image capturing system. Our data shows, that the software was able to accurately calculate the proportion of psoriatic skin surface as well as the severity of erythema, induration, and desquamation by anatomic region. In a pilot clinical validation the time-efficient technology showed a high reproducibility and high levels of agreement to results attained by PASI-trained physicians. Therefore, automated computer-guided PASI measurements hold the promise of significantly reducing the physicians' workload while ensuring a high level of reproducibility and standardization.
Indexed as
Identifiers
30390142What 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.