AIMC Topic: Wet Macular Degeneration
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Predicting response to anti-VEGF therapy in neovascular age-related macular degeneration using random forest and SHAP algorithms.
Photodiagnosis and photodynamic therapy
Jun 1, 2025
PURPOSE: This study aimed to establish and validate a prediction model based on machine learning methods and SHAP algorithm to predict response to anti-vascular endothelial growth factor (VEGF) therapy in neovascular age-related macular degeneration ...
Retrospective Studies
Female
Aged
Aged, 80 and over
Male
Humans
Machine Learning
Algorithms
Vascular Endothelial Growth Factor A
Macular Degeneration
Photochemotherapy
Wet Macular Degeneration
Choroidal Neovascularization
Middle Aged
Angiogenesis Inhibitors
Tomography, Optical Coherence
Random Forest
GENERATIVE DEEP LEARNING APPROACH TO PREDICT POSTTREATMENT OPTICAL COHERENCE TOMOGRAPHY IMAGES OF AGE-RELATED MACULAR DEGENERATION AFTER 12 MONTHS.
Retina (Philadelphia, Pa.)
Jun 1, 2025
PURPOSE: Predicting long-term anatomical responses in neovascular age-related macular degeneration patients is critical for patient-specific management. This study validates a generative deep learning model to predict 12-month posttreatment optical c...
Humans
Follow-Up Studies
Wet Macular Degeneration
Male
Vascular Endothelial Growth Factor A
Retrospective Studies
Deep Learning
Fluorescein Angiography
Visual Acuity
Intravitreal Injections
Time Factors
Female
Tomography, Optical Coherence
Angiogenesis Inhibitors
Macula Lutea
Aged
Fundus Oculi
Ranibizumab
Aged, 80 and over
Prediction of Post-Treatment Visual Acuity in Age-Related Macular Degeneration Patients With an Interpretable Machine Learning Method.
Translational vision science & technology
Sep 3, 2024
PURPOSE: We evaluated the features predicting visual acuity (VA) after one year in neovascular age-related macular degeneration (nAMD) patients.
ARTIFICIAL INTELLIGENCE-ENHANCED ANALYSIS OF RETINAL VASCULATURE IN AGE-RELATED MACULAR DEGENERATION.
Retina (Philadelphia, Pa.)
Sep 1, 2024
PURPOSE: To investigate associations between quantitative vascular measurements derived from intravenous fluorescein angiography (IVFA) and baseline characteristics on optical coherence tomography (OCT) in neovascular age-related macular degeneration...
DEEP LEARNING FOR AUTOMATIC PREDICTION OF EARLY ACTIVATION OF TREATMENT-NAIVE NONEXUDATIVE MACULAR NEOVASCULARIZATIONS IN AGE-RELATED MACULAR DEGENERATION.
Retina (Philadelphia, Pa.)
Aug 1, 2024
BACKGROUND: Around 30% of nonexudative macular neovascularizations exudate within 2 years from diagnosis in patients with age-related macular degeneration. The aim of this study is to develop a deep learning classifier based on optical coherence tomo...
Application of Deep Learning for Automated Detection of Polypoidal Choroidal Vasculopathy in Spectral Domain Optical Coherence Tomography.
Translational vision science & technology
Oct 3, 2022
OBJECTIVE: To develop an automated polypoidal choroidal vasculopathy (PCV) screening model to distinguish PCV from wet age-related macular degeneration (wet AMD).
DEVELOPMENT AND VALIDATION OF AN EXPLAINABLE ARTIFICIAL INTELLIGENCE FRAMEWORK FOR MACULAR DISEASE DIAGNOSIS BASED ON OPTICAL COHERENCE TOMOGRAPHY IMAGES.
Retina (Philadelphia, Pa.)
Mar 1, 2022
PURPOSE: To develop and validate an artificial intelligence framework for identifying multiple retinal lesions at image level and performing an explainable macular disease diagnosis at eye level in optical coherence tomography images.
Diagnosis of Polypoidal Choroidal Vasculopathy From Fluorescein Angiography Using Deep Learning.
Translational vision science & technology
Feb 1, 2022
PURPOSE: To differentiate polypoidal choroidal vasculopathy (PCV) from choroidal neovascularization (CNV) and to determine the extent of PCV from fluorescein angiography (FA) using attention-based deep learning networks.
IMPACT OF RESIDUAL SUBRETINAL FLUID VOLUMES ON TREATMENT OUTCOMES IN A SUBRETINAL FLUID-TOLERANT TREAT-AND-EXTEND REGIMEN.
Retina (Philadelphia, Pa.)
Nov 1, 2021
PURPOSE: To investigate associations between residual subretinal fluid (rSRF) volumes, quantified using artificial intelligence and treatment outcomes in a subretinal fluid (SRF)-tolerant treat-and-extend (T&E) regimen in neovascular age-related macu...
Vascular Endothelial Growth Factor A
Intravitreal Injections
Fluorescein Angiography
Ranibizumab
Follow-Up Studies
Visual Acuity
Tomography, Optical Coherence
Fundus Oculi
Wet Macular Degeneration
Subretinal Fluid
Drug Tolerance
Prospective Studies
Humans
Angiogenesis Inhibitors
Artificial Intelligence
Treatment Outcome
Artificial intelligence-based predictions in neovascular age-related macular degeneration.
Current opinion in ophthalmology
Sep 1, 2021
PURPOSE OF REVIEW: Predicting treatment response and optimizing treatment regimen in patients with neovascular age-related macular degeneration (nAMD) remains challenging. Artificial intelligence-based tools have the potential to increase confidence ...
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