AI Workflow, External Validation, and Development in Eye Disease Diagnosis.

ABSTRACT:

Importance

Timely disease diagnosis is challenging due to limited clinical availability and growing burdens. Although artificial intelligence (AI) has shown expert-level diagnostic accuracy, a lack of downstream accountability, including workflow integration, external validation, and further development, continues to hinder its clinical adoption.

Objective

To address gaps in the downstream accountability of medical AI through a case study on age-related macular degeneration (AMD) diagnosis and severity classification.

Design, setting, and participants

This diagnostic study developed and evaluated an AI-assisted diagnostic and classification workflow for AMD. Four rounds of diagnostic assessments (accuracy and time) were conducted with 24 clinicians from 12 institution

SUBMITTER: Chen Q 

PROVIDER: S-EPMC12268484 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature