Automated artificial intelligence-based system for clinical follow-up of patients with age-related macular degeneration.

ABSTRACT:

Purpose

In this study, we investigate the potential of a novel artificial intelligence-based system for autonomous follow-up of patients treated for neovascular age-related macular degeneration (AMD).

Methods

A temporal deep learning model was trained on a data set of 84 489 optical coherence tomography scans from AMD patients to recognize disease activity, and its performance was compared with a published non-temporal model trained on the same data (Acta Ophthalmol, 2021). An autonomous follow-up system was created by augmenting the AI model with deterministic logic to suggest treatment according to the observe-and-plan regimen. To validate the AI-based system, a data set comprising clinical decisions and imaging data from 200 follow-up consultations was collected prospecti

SUBMITTER: Potapenko I 

PROVIDER: S-EPMC9790353 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature