Supplementary material — AI-assisted ultrasound classification of hidradenitis suppurativa (retrospective multicenter pilot study)

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). 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).