Physician Level Assessment of Hirsute Women and of Their Eligibility for Laser Treatment With Deep Learning.

ABSTRACT:

Objectives

Hirsutism is a widespread condition affecting 5%-15% of females. Laser treatment of hirsutism has the best long-term effect. Patients with nonpigmented or nonterminal hairs are not eligible for laser treatment, and the current patient journey needed to establish eligibility for laser hair removal is problematic in many health-care systems.

Methods

In this study, we compared the ability to assess eligibility for laser hair removal of health-care professionals and convolutional neural network (CNN)-based models.

Results

The CNN ensemble model, synthesized from the outputs of five individual CNN models, reached an eligibility assessment accuracy of 0.52 (95% CI: 0.42-0.60) and a κ of 0.20 (95% CI: 0.13-0.27), taking a consensus expert label as reference. For c

SUBMITTER: Thomsen K 

PROVIDER: S-EPMC11776445 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature