[HTML][HTML] Trustworthy AI: closing the gap between development and integration of AI systems in ophthalmic practice

C González-Gonzalo, EF Thee, CCW Klaver… - Progress in retinal and …, 2022 - Elsevier
An increasing number of artificial intelligence (AI) systems are being proposed in
ophthalmology, motivated by the variety and amount of clinical and imaging data, as well as …

Automated deep learning-based AMD detection and staging in real-world OCT datasets (PINNACLE study report 5)

O Leingang, S Riedl, J Mai, GS Reiter, G Faustmann… - Scientific reports, 2023 - nature.com
Real-world retinal optical coherence tomography (OCT) scans are available in abundance
in primary and secondary eye care centres. They contain a wealth of information to be …

Few-shot out-of-distribution detection for automated screening in retinal OCT images using deep learning

T Araújo, G Aresta, U Schmidt-Erfurth, H Bogunović - Scientific Reports, 2023 - nature.com
Deep neural networks have been increasingly proposed for automated screening and
diagnosis of retinal diseases from optical coherence tomography (OCT), but often provide …

Transformer-based end-to-end classification of variable-length volumetric data

M Oghbaie, T Araújo, T Emre, U Schmidt-Erfurth… - … Conference on Medical …, 2023 - Springer
The automatic classification of 3D medical data is memory-intensive. Also, variations in the
number of slices between samples is common. Naïve solutions such as subsampling can …

A Deep Learning Network for Accurate Retinal Multidisease Diagnosis Using Multiview Fusion of En Face and B-Scan Images: A Multicenter Study

C Ou, X Wei, L An, J Qin, M Zhu, M **… - … Vision Science & …, 2024 - tvst.arvojournals.org
Purpose: Accurate diagnosis of retinal disease based on optical coherence tomography
(OCT) requires scrutiny of both B-scan and en face images. The aim of this study was to …