Upload README.md

README.md

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----
-license: other
-license_name: lh2-data-labs-commercial
-license_link: LICENSE
----
+---
+language:
+  - en
+license: other
+license_name: lh2-data-labs-commercial
+license_link: LICENSE.md
+task_categories:
+  - tabular-classification
+  - text-classification
+tags:
+  - medical
+  - dermatology
+  - skin-disease
+  - longitudinal
+  - south-asian
+  - fitzpatrick
+  - psoriasis
+  - eczema
+  - vitiligo
+  - clinical-photography
+  - prescriptions
+  - lab-panels
+  - multimodal
+  - ai-training
+pretty_name: "LH2 Data — Longitudinal Dermatology Atlas (South Asian Skin)"
+size_categories:
+  - 10K<n<100K
+---
+
+# LH2 Data — Longitudinal Dermatology Atlas
+
+**A longitudinal multimodal dermatology dataset with real-world per-patient follow-up across the full medical dermatology spectrum — not isolated snapshots, not cosmetic procedures. South Asian skin types at scale.**
+
+---
+
+## Dataset Summary
+
+Most dermatology AI datasets are cross-sectional snapshots predominantly representing Fitzpatrick I–III skin types. This dataset inverts both limitations: it provides **longitudinal clinical records** with multi-year per-patient follow-up (5+ years for mature cohorts) and is anchored entirely in **South Asian populations** (Fitzpatrick IV–VI), addressing the well-documented skin-type bias in dermatology AI.
+
+This sample contains structured visit-level metadata for 10 de-identified patients across 197 clinical visits, demonstrating the longitudinal schema. The complete dataset includes 60,000+ longitudinal records with active enrolment ongoing.
+
+**This sample is metadata-only.** Clinical photography (300+ high-resolution images per patient across anatomical regions per visit) is available under gated access with a signed Data Use Agreement.
+
+## Cohort at a Glance
+
+| Dimension | Scale |
+|---|---|
+| **Longitudinal Records** | 60,000+ (sample: 197 visits across 10 patients) |
+| **Photos per Patient** | 300+ across anatomical regions per visit |
+| **Longitudinal Depth** | 5+ years follow-up for mature cohorts |
+| **Fitzpatrick Coverage** | IV, V, VI (South Asian skin types) |
+| **Disease Focus** | Chronic inflammatory, autoimmune, pigmentary, acne spectrum |
+
+## Disease Coverage
+
+| Category | Conditions |
+|---|---|
+| **Chronic Inflammatory** | Psoriasis, Eczema / Atopic Dermatitis, Lichen Planus |
+| **Acne Spectrum** | Hidradenitis Suppurativa, Severe Acne Vulgaris |
+| **Autoimmune / Immunobullous** | Pemphigus Vulgaris, Bullous Pemphigoid, Cutaneous Lupus |
+| **Pigmentary Disorders** | Vitiligo |
+| **Hair Disorders** | Alopecia Areata |
+
+## Data Modalities
+
+| Modality | Description | Availability |
+|---|---|---|
+| **Clinical Photography** | 300+ DSLR high-resolution images per patient across anatomical regions per visit. Longitudinal series showing disease progression and treatment response. | Gated (DUA required) |
+| **Prescriptions & Treatment Regimens** | Full pharmacotherapy stack — topicals, immunosuppressants, biologics, isotretinoin. Dosing, duration, and switches documented per visit. | In this sample |
+| **Serial Lab Monitoring** | CBC, LFT, renal, lipid, autoimmune, and biologic-screening panels per visit. | In this sample |
+| **Visit-Level Metadata** | Date, severity assessment, PASI score (psoriasis), anatomical regions, photo counts, treatment response. | In this sample |
+| **Multimodal Linked** | Photography, prescriptions, and labs — joined per patient and visit. | Full dataset |
+
+## Visit Record Schema (16 fields)
+
+| Field | Type | Description |
+|---|---|---|
+| `patient_id` | string | De-identified patient identifier |
+| `visit_number` | int | Sequential visit number (1, 2, 3...) |
+| `visit_date` | string | Date of clinical visit (YYYY-MM-DD) |
+| `diagnosis` | string | Primary dermatological diagnosis |
+| `disease_category` | string | Condition category (chronic_inflammatory / autoimmune / pigmentary / acne_spectrum / hair_disorder) |
+| `fitzpatrick_type` | string | Fitzpatrick skin type (IV / V / VI) |
+| `age_at_first_visit` | int | Patient age at first recorded visit |
+| `sex` | string | Male / Female |
+| `severity` | string | Clinical severity assessment (Mild / Moderate / Severe / Very Severe) |
+| `pasi_score` | float | Psoriasis Area and Severity Index (psoriasis patients only; null otherwise) |
+| `photos_taken` | int | Number of clinical photographs taken at this visit |
+| `anatomical_regions` | string | Pipe-separated list of anatomical regions photographed |
+| `current_medication` | string | Current pharmacotherapy regimen |
+| `lab_panels` | string | Pipe-separated list of lab panels ordered at this visit |
+| `follow_up_months` | int | Months since first visit |
+| `treatment_response` | string | Clinical response assessment (Improving / Stable / Worsening / Flare / Remission) |
+
+## Why This Dataset Matters
+
+Existing dermatology datasets on HuggingFace and elsewhere share three structural limitations that this dataset addresses directly:
+
+**Cross-sectional vs. Longitudinal.** HAM10000, Fitzpatrick17k, DDI, and Derm1M are all single-visit snapshot datasets. They cannot capture disease trajectory, treatment response over time, medication switches, or the visual progression of chronic conditions. This dataset provides 10–30 visits per patient spanning 2–5+ years.
+
+**Fitzpatrick I–III bias.** The majority of training data for skin AI models comes from populations with lighter skin types. Per the 2025 SkinMap audit, Fitzpatrick V–VI representation in the largest public datasets is approximately 5.8%. This dataset is 100% Fitzpatrick IV–VI.
+
+**Cosmetic vs. Medical.** Many skin datasets mix cosmetic dermatology (mole classification, benign lesion detection) with medical dermatology. This dataset covers exclusively medically-managed conditions requiring systemic therapy — psoriasis, pemphigus, HS, cutaneous lupus — where longitudinal treatment data is critical.
+
+## Key Differentiators
+
+- **Longitudinal**: 5+ years follow-up with 300+ photos per patient — not single-visit snapshots
+- **South Asian skin**: 100% Fitzpatrick IV–VI — directly addresses the most documented bias in dermatology AI
+- **Medical focus**: Chronic inflammatory, autoimmune, and immunobullous conditions requiring systemic therapy
+- **Multimodal linked**: Photography + prescriptions + serial lab panels joined per patient and visit
+- **Full pharmacotherapy stack**: Topicals, immunosuppressants (methotrexate, cyclosporine, MMF), biologics (secukinumab, adalimumab), isotretinoin — real treatment trajectories, not just diagnostic labels
+
+## IP & Compliance
+
+- Full commercial and AI/ML training rights under exclusive licensing agreement
+- De-identified patient data — no personally identifiable information
+- Clinical photography available under gated access with signed Data Use Agreement
+- Re-identification of patients from clinical photographs is expressly prohibited
+- Compliant with India's DPDP Act 2023 for data licensing and cross-border transfer
+
+## Citation
+
+```bibtex
+@dataset{lh2_derma_2025,
+  title={LH2 Data — Longitudinal Dermatology Atlas},
+  author={LH2 Data Labs},
+  year={2025},
+  publisher={Hugging Face},
+  note={60K+ longitudinal dermatology records with South Asian Fitzpatrick IV-VI coverage}
+}
+```