Studies in health technology and informatics
May 25, 2022
Deep Learning methods have become dominant in various fields of medical imaging, including ophthalmology. In this preliminary study, we investigated a method based on Convolutional Neural Network for the identification of drusen and macular hole from...
PURPOSE: Prior studies have demonstrated the significance of specific cis-regulatory variants in retinal disease; however, determining the functional impact of regulatory variants remains a major challenge. In this study, we utilized a machine learni...
Translational vision science & technology
Mar 2, 2022
PURPOSE: The purpose of this study was to design an automated algorithm that can detect fluorescence leakage accurately and quickly without the use of a large amount of labeled data.
PURPOSE: We aimed to develop and test a deep-learning system to perform image quality and diabetic macular ischemia (DMI) assessment on optical coherence tomography angiography (OCTA) images.
PURPOSE: To analyze the effect of transfer learning for classification of diabetic retinopathy (DR) by fundus photography and select retinal diseases by spectral domain optical coherence tomography (SD-OCT).
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Retinopathy screening is a non-invasive method to collect retinal images and neovascularization detection from retinal images plays a significant role on the identification and classification of diabetes retinopathy. In this paper, an efficient deep ...
BACKGROUND: Medical artificial intelligence (AI) has entered the clinical implementation phase, although real-world performance of deep-learning systems (DLSs) for screening fundus disease remains unsatisfactory. Our study aimed to train a clinically...
Disease classification and lesion segmentation of retinal optical coherence tomography images play important roles in ophthalmic computer-aided diagnosis. However, existing methods achieve the two tasks separately, which is insufficient for clinical ...
PURPOSE OF REVIEW: To review the current status of artificial intelligence systems in ophthalmology and highlight the steps required for clinical translation of artificial intelligence into personalized health care (PHC) in retinal disease.
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