Teledermatology to Support Self-Care in Chronic Spontaneous Urticaria
Bibliographic record
Abstract
Unlabelled: Chronic spontaneous urticaria (CSU) is an autoimmune prompted skin disorder, whose hallmarks include the unpredictable onset of hives and itch. Symptom duration typically exceed 6 weeks, and flares can occur for up to 5 years or longer if untreated, impacting potentially any area of the body. The absence of obvious triggers and the variation in onset frequency often delays formal diagnosis which on average is approximately 2 years from first presentation. Initial standard of care is the use of low through to higher strength antihistamines in the first instance, with eventual escalation to prescription anti-inflammatory agents and potentially biologics once patients are under managed care. The societal impacts of delays in diagnosis are marked, with data suggesting CSU impacts up to 1% of the population, primarily of working age and with twice the prevalence in women. Herein, we advocate for the deployment of smartphone imaging and generative artificial intelligence technology to improve detection and early management of CSU through integrated self-care approaches. Such approaches embodying the tenets of P4 personalized medicine could have sustained impact on the disease through awareness campaigns, reducing the burden on the dermatology community and facilitating earlier access to curative therapeutic interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".