Development and Testing of an AI Assistant App for Managing Atopic Dermatitis Using Treat to Target Strategy

What this Trial Is About

Atopic dermatitis AD is a long-lasting skin condition marked by repeated rashes and itching, which seriously impacts patients quality of life and creates a significant economic burden. Researchers are evaluating an Artificial Intelligence assistant decision-making system AIADMS app that integrates the Treat to Target T2T strategy to improve disease control and clinical outcomes for patients with moderate to severe AD. This project aims to develop, train, and test the AIADMS app through clinical trials to verify its effectiveness and safety in managing AD. The AIADMS app is designed for both patients and clinicians with features such as reminders, photo uploads, self-evaluation, and data management. The app uses a deep learning model trained on over 10,000 clinical images to assess AD severity and clinical signs. Participants in the treatment group will use the app for disease management and be followed up at scheduled times up to 12 months after treatment, while the control group will receive routine face-to-face care. The app supports Android and iOS and provides automated assessments using tools like EASI, POEM, SCORAD, PP-NRS, and DLQI to help patients and clinicians monitor progress. Participants will have follow-up visits at 2 weeks, 4 weeks, 8 weeks, 12 weeks, 6 months, and 12 months after treatment. During these visits, evaluations using five treatment objectives will be performed. Data collected will include clinical scores, economic consumption, and satisfaction evaluations. The primary outcome is the overall efficiency rate of treatment objectives at 12 weeks. The study also involves tracking safety and patient adherence, with the entire study period lasting up to 12 months.

AI App for Management of Atopic Dermatitis