Multi-task AI models in dermatology: Overcoming critical clinical translation challenges for enhanced skin lesion diagnosis.

ABSTRACT:

Background

The surge in AI models for diagnosing skin lesions through image analysis is notable, yet their clinical implementation faces challenges. Common limitations include an over reliance on dermoscopy, lack of real-world applicability when only binary output (e.g. benign/malignant) is offered and low accuracy when faced with rare skin conditions.

Objectives

To address these common constraints associated with limited diagnostic output, and applicability to real-world settings.

Methods

We developed an All-In-One Hierarchical-Out of Distribution-Clinical Triage (HOT) AI model for skin lesion analysis. Trained on a large dataset of ~208,000 lesion images, our HOT AI model generates three outputs: a hierarchical three-level prediction, an alert for out-of-distributio

SUBMITTER: Mehta D 

PROVIDER: S-EPMC12645183 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature