AIMC Topic: Retina
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Artificial intelligence-based prediction of neurocardiovascular risk score from retinal swept-source optical coherence tomography-angiography.
Scientific reports
Nov 7, 2024
The recent rise of artificial intelligence represents a revolutionary way of improving current medical practices, including cardiovascular (CV) assessment scores. Retinal vascular alterations may reflect systemic processes such as the presence of CV ...
Multi-modal representation learning in retinal imaging using self-supervised learning for enhanced clinical predictions.
Scientific reports
Nov 5, 2024
Self-supervised learning has become the cornerstone of building generalizable and transferable artificial intelligence systems in medical imaging. In particular, contrastive representation learning techniques trained on large multi-modal datasets hav...
Self-supervised based clustering for retinal optical coherence tomography images.
Eye (London, England)
Oct 28, 2024
BACKGROUND: In response to the inadequacy of manual analysis in meeting the rising demand for retinal optical coherence tomography (OCT) images, a self-supervised learning-based clustering model was implemented.
Grading of diabetic retinopathy using a pre-segmenting deep learning classification model: Validation of an automated algorithm.
Acta ophthalmologica
Oct 19, 2024
PURPOSE: To validate the performance of autonomous diabetic retinopathy (DR) grading by comparing a human grader and a self-developed deep-learning (DL) algorithm with gold-standard evaluation.
Privacy-Preserving Technology Using Federated Learning and Blockchain in Protecting against Adversarial Attacks for Retinal Imaging.
Ophthalmology
Oct 16, 2024
PURPOSE: Collaboration provides valuable data for robust artificial intelligence (AI) model development. Federated learning (FL) is a privacy-enhancing technology that allows collaboration while respecting privacy via the development of models withou...
Artificial intelligence-based analysis of retinal fluid volume dynamics in neovascular age-related macular degeneration and association with vision and atrophy.
Eye (London, England)
Oct 15, 2024
BACKGROUND/OBJECTIVES: To characterise morphological changes in neovascular age-related macular degeneration (nAMD) during anti-angiogenic therapy and explore relationships with best-corrected visual acuity (BCVA) and development of macular atrophy (...
Application of a deep-learning marker for morbidity and mortality prediction derived from retinal photographs: a cohort development and validation study.
The lancet. Healthy longevity
Sep 30, 2024
BACKGROUND: Biological ageing markers are useful to risk stratify morbidity and mortality more precisely than chronological age. In this study, we aimed to develop a novel deep-learning-based biological ageing marker (referred to as RetiPhenoAge here...
Validation of a deep learning model for automatic detection and quantification of five OCT critical retinal features associated with neovascular age-related macular degeneration.
The British journal of ophthalmology
Sep 20, 2024
PURPOSE: To develop and validate a deep learning model for the segmentation of five retinal biomarkers associated with neovascular age-related macular degeneration (nAMD).
An attentional mechanism model for segmenting multiple lesion regions in the diabetic retina.
Scientific reports
Sep 12, 2024
Diabetic retinopathy (DR), a leading cause of blindness in diabetic patients, necessitates the precise segmentation of lesions for the effective grading of lesions. DR multi-lesion segmentation faces the main concerns as follows. On the one hand, ret...
Validation of neuron activation patterns for artificial intelligence models in oculomics.
Scientific reports
Sep 9, 2024
Recent advancements in artificial intelligence (AI) have prompted researchers to expand into the field of oculomics; the association between the retina and systemic health. Unlike conventional AI models trained on well-recognized retinal features, th...
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