PURPOSE: To evaluate various supervised machine learning (ML) statistical models to predict anatomical outcomes after macular hole (MH) surgery using preoperative optical coherence tomography (OCT) features.
Biomedical physics & engineering express
Dec 20, 2024
In this paper, an automated feature selection (FS) method is presented to optimize machine learning (ML) models' performances, enhancing early keratoconus screening. A total of 448 parameters were analyzed from a dataset comprising 3162 observations ...
Inability to express the confidence level and detect unseen disease classes limits the clinical implementation of artificial intelligence in the real world. We develop a foundation model with uncertainty estimation (FMUE) to detect 16 retinal conditi...
Journal of the European Academy of Dermatology and Venereology : JEADV
Dec 17, 2024
BACKGROUND: Ablative fractional photothermolysis serves as an excellent in vivo model for studying wound healing. The advent of non-invasive imaging devices, such as line-field confocal optical coherence tomography (LC-OCT), enhances this model by en...
PURPOSE: The objective of this study is to estimate the area of the Foveal Avascular Zone (FAZ) from B-scan OCT images using machine learning algorithms.
Medical & biological engineering & computing
Dec 13, 2024
Optical coherence tomography angiography (OCTA) is a novel non-invasive retinal vessel imaging technique that can display high-resolution 3D vessel structures. The quantitative analysis of retinal vessel morphology plays an important role in the auto...
BACKGROUND: Investigate retinal fluid changes via a novel deep-learning algorithm in real-world patients receiving faricimab for the treatment of neovascular age-related macular degeneration (nAMD).
The use of deep learning for OCT image classification could enhance the diagnosis and monitoring of retinal diseases. However, challenges like variability in retinal abnormalities, noise, and artifacts in OCT images limit its clinical use. Our study ...
Middle East African journal of ophthalmology
Dec 2, 2024
Numerous artificial intelligence (AI) models, including deep learning techniques, are being developed to segment choroids in optical coherence tomography (OCT) images. However, there is a need for consensus on which specific models to use, requiring ...
BACKGROUND/AIMS: To design a deep learning (DL) model for the detection of glaucoma progression with a longitudinal series of macular optical coherence tomography angiography (OCTA) images.
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