Data · dataset · 2026
Supplementary material — AI-assisted ultrasound classification of hidradenitis suppurativa (retrospective multicenter pilot study)
Listed in Teesside University Research Data Repository
This dataset contains supplementary material accompanying the manuscript "Artificial Intelligence–Assisted Ultrasound for Hidradenitis Suppurativa: Results from a Retrospective Multicenter Pilot Study," submitted to the Journal of the American Academy of Dermatology (JAAD).
Description
The study is a retrospective, multicenter pilot evaluation of a YOLOv26-based AI system for automated ultrasound classification of hidradenitis suppurativa (HS) lesions, using a novel macro-micro annotation strategy, conducted across centers in Spain, Chile, and Italy in collaboration with the Department of Computer Science and Artificial Intelligence, Universidad de Granada.
Included files: These materials exceed the main-text figure/table allotment permitted by JAAD and are provided for editor/reviewer reference and for readers seeking full per-fold detail. All ultrasound images were fully anonymized prior to analysis; no identifiable patient information is included. Study approved by the Research Ethics Committee of the Province of Granada, Spain (Protocol Code: SICEIA-2024-001528).
Links
Where it is published
- DOI doi.org/10.17632/tnx2mv85p2.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Artificial intelligence · Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
Provenance · 1 source records, 14 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/tnx2mv85p2.1 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:group:4602 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Artificial Intelligence'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:image | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (65%) |
| concepts[modality].local:modality:tabular | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |