This study is a cross-sectional, observational investigation designed to develop and validate a noninvasive ocular imaging-based predictive model for major inflammatory skin diseases, including psoriasis, atopic dermatitis, and urticaria. Grounded in Traditional Chinese Medicine (TCM) ocular diagnostic theory and integrated with advanced computer vision techniques, the study aims to establish objective, quantifiable biomarkers derived from scleral and bulbar conjunctival images.

Approximately 950 participants (patients with psoriasis, atopic dermatitis, urticaria, and healthy controls) will be recruited from a tertiary academic hospital. Standardized high-resolution ocular images will be collected alongside comprehensive clinical, demographic, and comorbidity data. Disease severity will be assessed using validated clinical scoring systems (e.g., PASI, EASI, UAS7, DLQI).

Image analysis will combine traditional radiomics feature extraction with deep learning architectures, including a Vision State-Space (VMamba) module for global-local feature representation and a Multi-Gate Mixture-of-Experts (MMoE) framework for multi-task learning. The model is designed to simultaneously perform disease classification and predict comorbidity risks (such as metabolic syndrome, hepatic insulin resistance, and recurrence risk).

Primary outcomes include characterization of ocular feature patterns associated with inflammatory skin diseases. Secondary outcomes include correlations between ocular image-derived features and clinical severity indices. Model performance will be evaluated using ROC curves, AUC, calibration analysis, and decision curve analysis.

This study aims to provide an objective, digitalized, and clinically applicable ocular biomarker framework to support early diagnosis, risk stratification, and comorbidity screening in inflammatory skin diseases.

Inclusion Criteria:

For patients with inflammatory skin disease:

Clinical diagnosis of one of the three target inflammatory skin diseases (psoriasis, atopic dermatitis, or urticaria).

Age ≥ 18 and ≤ 65 years, any sex.

Understands and signs informed consent.

For healthy controls:

Do not meet diagnostic criteria for any of the three inflammatory skin diseases above.

Age ≥ 18 and ≤ 65 years, any sex.

Understands and signs informed consent.

Exclusion Criteria:

For patients with inflammatory skin disease:

Exclude any subject meeting any of the following:

Refusal to undergo examinations.

Presence of acute/active infectious ocular disease (e.g., viral keratoconjunctivitis).

Corneal perforation or high-risk perforation where contact procedures cause severe photophobia, eye pain, inability to keep eyes open or fixate.

Nystagmus or other conditions that prevent fixation.

Pupillary non-dilation (e.g., posterior synechiae) that precludes fundus imaging.

Severe eyelid lesions (e.g., marked swelling, ectropion, entropion) that prevent globe exposure.

Participation in other clinical trials within the previous 3 months or concurrent participation in other interventional studies.

• Healthy control - exclusion criteria

Exclude any subject meeting any of the following:

Presence of other skin diseases that could affect study assessments (e.g., atopic dermatitis, urticaria, scabies).

Refusal to undergo examinations.

Acute/active infectious ocular disease (e.g., viral keratoconjunctivitis).

Corneal perforation or high-risk perforation that causes severe photophobia, eye pain, inability to keep eyes open or fixate during contact procedures.

Nystagmus or other reasons preventing fixation.

Pupillary non-dilation (e.g., posterior synechiae) that prevents fundus imaging.

Participation in other clinical studies within the previous 3 months or currently participating in other clinical trials.

As an exploratory cross-sectional study involving high-dimensional image-omics modeling, we plan to enlarge the sample size. We intend to recruit 200 cases each of psoriasis, atopic dermatitis, and urticaria, and 150 healthy controls. The dataset will be split into training and internal validation sets at an 8:2 ratio. An external independent validation cohort of 200 subjects is planned. The total sample size is therefore approximately 950 participants.