526 citations · 783 across the 36 of their papers we have counts for
6 papers · 1 filter
Patch Progression Masked Autoencoder with Fusion CNN Network for Classifying Evolution Between Two Pairs of 2D OCT Slices
Philippe Zhang, Weili Jiang, Yihao Li +13
Age-related Macular Degeneration (AMD) is a prevalent eye condition affecting visual acuity. Anti-vascular endothelial growth factor (anti-VEGF) treatments have been effective in s…
Deep Learning for Retinal Degeneration Assessment: A Comprehensive Analysis of the MARIO Challenge
Rachid Zeghlache, Ikram Brahim, Pierre-Henri Conze +47
The MARIO challenge, held at MICCAI 2024, focused on advancing the automated detection and monitoring of age-related macular degeneration (AMD) through the analysis of optical cohe…
Suicide Risk Assessment Using Multimodal Speech Features: A Study on the SW1 Challenge Dataset
Ambre Marie, Ilias Maoudj, Guillaume Dardenne +1
The 1st SpeechWellness Challenge conveys the need for speech-based suicide risk assessment in adolescents. This study investigates a multimodal approach for this challenge, integra…
Acoustic and Machine Learning Methods for Speech-Based Suicide Risk Assessment: A Systematic Review
Ambre Marie, Marine Garnier, Thomas Bertin +4
Suicide remains a public health challenge, necessitating improved detection methods to facilitate timely intervention and treatment. This systematic review evaluates the role of Ar…
Deep learning-enabled prediction of surgical errors during cataract surgery: from simulation to real-world application
Maxime Faure, Pierre-Henri Conze, Béatrice Cochener +3
Real-time prediction of technical errors from cataract surgical videos can be highly beneficial, particularly for telementoring, which involves remote guidance and mentoring throug…
Context-Aware Vision Language Foundation Models for Ocular Disease Screening in Retinal Images
Lucie Berger, Mathieu Lamard, Philippe Zhang +6
Foundation models are large-scale versatile systems trained on vast quantities of diverse data to learn generalizable representations. Their adaptability with minimal fine-tuning m…