Using artificial intelligence to analyse the retinal vascular network: the future of cardiovascular risk assessment based on oculomics? A narrative review

L Arnould, F Meriaudeau, C Guenancia… - Ophthalmology and …, 2023 - Springer
The healthcare burden of cardiovascular diseases remains a major issue worldwide.
Understanding the underlying mechanisms and improving identification of people with a …

An overview of deep-learning-based methods for cardiovascular risk assessment with retinal images

RG Barriada, D Masip - Diagnostics, 2022 - mdpi.com
Cardiovascular diseases (CVDs) are one of the most prevalent causes of premature death.
Early detection is crucial to prevent and address CVDs in a timely manner. Recent advances …

[HTML][HTML] One-shot retinal artery and vein segmentation via cross-modality pretraining

D Shi, S He, J Yang, Y Zheng, M He - Ophthalmology science, 2024 - Elsevier
Purpose To perform one-shot retinal artery and vein segmentation with cross-modality artery-
vein (AV) soft-label pretraining. Design Cross-sectional study. Subjects The study included …

Translating color fundus photography to indocyanine green angiography using deep-learning for age-related macular degeneration screening

R Chen, W Zhang, F Song, H Yu, D Cao, Y Zheng… - NPJ digital …, 2024 - nature.com
Age-related macular degeneration (AMD) is the leading cause of central vision impairment
among the elderly. Effective and accurate AMD screening tools are urgently needed …

[HTML][HTML] Translation of color fundus photography into fluorescein angiography using deep learning for enhanced diabetic retinopathy screening

D Shi, W Zhang, S He, Y Chen, F Song, S Liu… - Ophthalmology …, 2023 - Elsevier
Purpose To develop and validate a deep learning model that can transform color fundus
(CF) photography into corresponding venous and late-phase fundus fluorescein …

Eyefound: a multimodal generalist foundation model for ophthalmic imaging

D Shi, W Zhang, X Chen, Y Liu, J Yang… - arxiv preprint arxiv …, 2024 - arxiv.org
Artificial intelligence (AI) is vital in ophthalmology, tackling tasks like diagnosis,
classification, and visual question answering (VQA). However, existing AI models in this …

GWAS-by-subtraction reveals an IOP-independent component of primary open angle glaucoma

Y Huang, D Plotnikov, H Wang, D Shi, C Li… - Nature …, 2024 - nature.com
The etiology of primary open angle glaucoma is constituted by both intraocular pressure-
dependent and intraocular pressure-independent mechanisms. However, GWASs of traits …

FFA-GPT: an automated pipeline for fundus fluorescein angiography interpretation and question-answer

X Chen, W Zhang, P Xu, Z Zhao, Y Zheng, D Shi… - npj Digital …, 2024 - nature.com
Fundus fluorescein angiography (FFA) is a crucial diagnostic tool for chorioretinal diseases,
but its interpretation requires significant expertise and time. Prior studies have used Artificial …

Integrating oculomics with genomics reveals imaging biomarkers for preventive and personalized prediction of arterial aneurysms

Y Huang, C Li, D Shi, H Wang, X Shang, W Wang… - EPMA Journal, 2023 - Springer
Objective Arterial aneurysms are life-threatening but usually asymptomatic before requiring
hospitalization. Oculomics of retinal vascular features (RVFs) extracted from retinal fundus …

ICGA-GPT: report generation and question answering for indocyanine green angiography images

X Chen, W Zhang, Z Zhao, P Xu, Y Zheng… - British Journal of …, 2024 - bjo.bmj.com
Background Indocyanine green angiography (ICGA) is vital for diagnosing chorioretinal
diseases, but its interpretation and patient communication require extensive expertise and …