Quasi-distributed optical fiber hydrogen leakage detecting system based on bus chain topology structure.

INTRODUCTION

Alopecia treatment can improve patients' quality of life, but slow hair regrowth makes progress difficult to detect. Trichoscopic measurements (TMs; hair density, hairs/cm2; hair caliber, µm) provide an objective method for monitoring treatment response. Artificial intelligence (AI) enables trichoscopic analysis without hair clippings. This study examines the perspectives of alopecia patients regarding AI-driven trichoscopy.

METHODS

We conducted an IRB-approved survey study and chart review of 101 patients at the NYU Langone hair clinic undergoing AI-driven trichoscopy. Pre- and post-visit surveys measured self-perceived alopecia severity and quality-of-life impact before and after reviewing TMs with their dermatologist. Opinions regarding AI-driven trichoscopy were assessed via Likert scales. Demographics, medical history, and clinician-assessed severity were extracted from medical charts.

RESULTS

Most participants were female (74.3%), white (73.3%), and had nonscarring alopecia (89%). After reviewing TMs, 33.7% of participants reported feeling less bothered by their alopecia, 39.6% perceived reduced severity, and 54.5% noted increased treatment motivation. Among follow-up patients, concordance between patient and physician assessments of interval change in hair loss improved after viewing TMs (p = 0.0075). Patients endorsed enhanced alopecia care and greater confidence in treatment recommendations with the use of AI-driven trichoscopy.

CONCLUSION

Patients with alopecia generally view AI-driven trichoscopy favorably, noting improved quality of care and greater motivation to continue therapy.