# Teledermatology to Support Self-Care in Chronic Spontaneous Urticaria

## TL;DR

This paper suggests using smartphone imaging and AI to help diagnose and manage chronic urticaria, a skin condition, earlier and more effectively.

## Contribution

The novel contribution is proposing teledermatology with AI for early detection and self-care in chronic spontaneous urticaria.

## Key findings

- CSU affects up to 1% of the population, mainly working-age individuals.
- Delayed diagnosis of CSU averages two years from initial symptoms.
- AI and smartphone imaging could improve early detection and reduce healthcare burden.

## Abstract

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.