Background: There is a scarcity of artificial intelligence models trained on frozen pathology. One way to expand the clinical utility of models trained on permanent pathology is by applying them to frozen sections and fine-tune based on weaknesses.
Objective: To qualitatively evaluate a deep learning model trained on permanent pathology to classify squamous cell carcinoma on Mohs surgery frozen sections to learn model shortcomings and inform retraining and fine-tuning.
Int J Womens Dermatol
June 2025
Background: Hidradenitis suppurativa (HS) is a chronic, recurrent inflammatory condition and is associated with significant psychosocial impacts on patient quality of life.
Objective: This study aimed to characterize the utilization of patient-reported outcomes (PROs) in HS clinical trials and their concordance with trial primary endpoints.
Methods: A systematic review of clinical trials was performed using the publicly available U.
Current validated lichen planus (LP) scoring systems are complicated and optimized for generalized, multi-site disease. There is a need for a validated, simple lesional assessment in LP. Herein, we repurpose and optimize the modified Composite Assessment of Index Lesion Severity (mCAILS) for LP and to validate the optimized lichen planus CAILS (lpCAILS).
View Article and Find Full Text PDFBACKGROUNDCutaneous lichen planus (LP) is a recalcitrant, difficult-to-treat, inflammatory skin disease characterized by pruritic, flat-topped, violaceous papules on the skin. Baricitinib is an oral Janus kinase (JAK) 1/2 inhibitor that interrupts the signaling pathway of IFN-γ, a cytokine implicated in the pathogenesis of LP.METHODSIn this phase II trial, 12 patients with cutaneous LP received 2 mg daily baricitinib for 16 weeks, accompanied by in-depth spatial, single-cell, and bulk transcriptomic profiling of pre- and posttreatment samples.
View Article and Find Full Text PDFJ Invest Dermatol
September 2024