AIMC Topic: Macular Edema
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A hybrid model for the detection of retinal disorders using artificial intelligence techniques.
Biomedical physics & engineering express
Jul 10, 2024
The prevalence of vision impairment is increasing at an alarming rate. The goal of the study was to create an automated method that uses optical coherence tomography (OCT) to classify retinal disorders into four categories: choroidal neovascularizati...
Applications of artificial intelligence in diagnosis of uncommon cystoid macular edema using optical coherence tomography imaging: A systematic review.
Survey of ophthalmology
Jun 27, 2024
Cystoid macular edema (CME) is a sight-threatening condition often associated with inflammatory and diabetic diseases. Early detection is crucial to prevent irreversible vision loss. Artificial intelligence (AI) has shown promise in automating CME di...
Correlation of limited-early-response status with 12-month CST, BVA, and machine learning-quantified retinal fluid in diabetic macular oedema in routine clinical practice.
Eye (London, England)
Jun 18, 2024
BACKGROUND/OBJECTIVES: Anti-VEGF treatment response in DMO has been measured by changes in the central subfield thickness (CST) and best visual acuity (BVA) outcomes at 3 months after initial treatment, termed early or limited early response (ER/LER)...
Automated machine learning model for fundus image classification by health-care professionals with no coding experience.
Scientific reports
May 6, 2024
To assess the feasibility of code-free deep learning (CFDL) platforms in the prediction of binary outcomes from fundus images in ophthalmology, evaluating two distinct online-based platforms (Google Vertex and Amazon Rekognition), and two distinct da...
Recognition of diabetic retinopathy and macular edema using deep learning.
Medical & biological engineering & computing
Apr 30, 2024
Diabetic retinopathy (DR) and diabetic macular edema (DME) are both serious eye conditions associated with diabetes and if left untreated, and they can lead to permanent blindness. Traditional methods for screening these conditions rely on manual ima...
A new intelligent system based deep learning to detect DME and AMD in OCT images.
International ophthalmology
Apr 23, 2024
Optical Coherence Tomography (OCT) is widely recognized as the leading modality for assessing ocular retinal diseases, playing a crucial role in diagnosing retinopathy while maintaining a non-invasive modality. The increasing volume of OCT images und...
OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods.
Scientific data
Apr 11, 2024
Optical coherence tomography (OCT) is a non-invasive imaging technique with extensive clinical applications in ophthalmology. OCT enables the visualization of the retinal layers, playing a vital role in the early detection and monitoring of retinal d...
[Authors' reply to the letter to the editor "Artificial intelligence and screening for visual impairment related to diabetic retinopathy and macular edema"].
Gaceta medica de Mexico
Apr 8, 2024
[Artificial intelligence and screening for visual impairment related to diabetic retinopathy and macular edema].
Gaceta medica de Mexico
Apr 3, 2024
Self-supervised category selective attention classifier network for diabetic macular edema classification.
Acta diabetologica
Mar 23, 2024
AIMS: This study aims to develop an advanced model for the classification of Diabetic Macular Edema (DME) using deep learning techniques. Specifically, the objective is to introduce a novel architecture, SSCSAC-Net, that leverages self-supervised lea...
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