AIMC Topic: Vascular Endothelial Growth Factor A

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Suitability of machine learning for atrophy and fibrosis development in neovascular age-related macular degeneration.

Acta ophthalmologica
PURPOSE: To assess the suitability of machine learning (ML) techniques in predicting the development of fibrosis and atrophy in patients with neovascular age-related macular degeneration (nAMD), receiving anti-VEGF treatment over a 36-month period.

Preliminary analysis of predicting the first recurrence in patients with neovascular age-related macular degeneration using deep learning.

BMC ophthalmology
BACKGROUND: To predict, using deep learning, the first recurrence in patients with neovascular age-related macular degeneration (nAMD) after three monthly loading injections of intravitreal anti-vascular endothelial growth factor (anti-VEGF).

Predicting Visual Acuity Responses to Anti-VEGF Treatment in the Comparison of Age-related Macular Degeneration Treatments Trials Using Machine Learning.

Ophthalmology. Retina
PURPOSE: To evaluate multiple machine learning (ML) models for predicting 2-year visual acuity (VA) responses to anti-vascular endothelial growth factor (anti-VEGF) treatment in the Comparison of Age-related Macular Degeneration (AMD) Treatments Tria...

Performance of retinal fluid monitoring in OCT imaging by automated deep learning versus human expert grading in neovascular AMD.

Eye (London, England)
PURPOSE: To evaluate the reliability of automated fluid detection in identifying retinal fluid activity in OCT scans of patients treated with anti-VEGF therapy for neovascular age-related macular degeneration by correlating human expert and automated...

Interpretable attention-based deep learning ensemble for personalized ovarian cancer treatment without manual annotations.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Inhibition of pathological angiogenesis has become one of the first FDA approved targeted therapies widely tested in anti-cancer treatment, i.e. VEGF-targeting monoclonal antibody bevacizumab, in combination with chemotherapy for frontline and mainte...

KFWC: A Knowledge-Driven Deep Learning Model for Fine-grained Classification of Wet-AMD.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Automated diagnosis using deep neural networks can help ophthalmologists detect the blinding eye disease wet Age-related Macular Degeneration (AMD). Wet-AMD has two similar subtypes, Neovascular AMD and Polypoidal Choroidal...

Correlation of vascular and fluid-related parameters in neovascular age-related macular degeneration using deep learning.

Acta ophthalmologica
PURPOSE: To identify correlations between the vascular characteristics of macular neovascularization (MNV) obtained by optical coherence tomography angiography (OCTA) and distinct retinal fluid volumes in neovascular age-related macular degeneration ...

Therapeutic response in the HAWK and HARRIER trials using deep learning in retinal fluid volume and compartment analysis.

Eye (London, England)
OBJECTIVES: To assess the therapeutic response to brolucizumab and aflibercept by deep learning/OCT-based analysis of macular fluid volumes in neovascular age-related macular degeneration.

Clinically applicable deep learning-based decision aids for treatment of neovascular AMD.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: Anti-vascular endothelial growth factor (Anti-VEGF) therapy is currently seen as the standard for treatment of neovascular AMD (nAMD). However, while treatments are highly effective, decisions for initial treatment and retreatment are often ...