AIMC Topic: Eye Diseases
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DETECTION AND LOCALIZATION OF RETINAL BREAKS IN ULTRAWIDEFIELD FUNDUS PHOTOGRAPHY USING a YOLO v3 ARCHITECTURE-BASED DEEP LEARNING MODEL.
Retina (Philadelphia, Pa.)
Oct 1, 2022
PURPOSE: We aimed to develop a deep learning model for detecting and localizing retinal breaks in ultrawidefield fundus (UWF) images.
A Multicenter Clinical Study of the Automated Fundus Screening Algorithm.
Translational vision science & technology
Jul 8, 2022
PURPOSE: To evaluate the effectiveness of automated fundus screening software in detecting eye diseases by comparing the reported results against those given by human experts.
Development and validation of an offline deep learning algorithm to detect vitreoretinal abnormalities on ocular ultrasound.
Indian journal of ophthalmology
Apr 1, 2022
PURPOSE: We describe our offline deep learning algorithm (DLA) and validation of its diagnostic ability to identify vitreoretinal abnormalities (VRA) on ocular ultrasound (OUS).
A Review on an Artificial Intelligence Based Ophthalmic Application.
Current pharmaceutical design
Jan 1, 2022
Artificial intelligence is the leading branch of technology and innovation. The utility of artificial intelligence in the field of medicine is also remarkable. From drug discovery and development to introducing products to the market, artificial inte...
Ocular Diseases Detection using Recent Deep Learning Techniques.
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
Early fundus screening is a cost-effective and efficient approach to reduce ophthalmic disease-related blindness in ophthalmology. Manual evaluation is time-consuming. Ophthalmic disease detection studies have shown interesting results thanks to the ...
Updates in deep learning research in ophthalmology.
Clinical science (London, England : 1979)
Oct 29, 2021
Ophthalmology has been one of the early adopters of artificial intelligence (AI) within the medical field. Deep learning (DL), in particular, has garnered significant attention due to the availability of large amounts of data and digitized ocular ima...
Referral for disease-related visual impairment using retinal photograph-based deep learning: a proof-of-concept, model development study.
The Lancet. Digital health
Jan 1, 2021
BACKGROUND: In current approaches to vision screening in the community, a simple and efficient process is needed to identify individuals who should be referred to tertiary eye care centres for vision loss related to eye diseases. The emergence of dee...
Outcomes of Adversarial Attacks on Deep Learning Models for Ophthalmology Imaging Domains.
JAMA ophthalmology
Nov 1, 2020
This study investigates whether adversarial attacks can confuse deep learning systems based on imaging domains.
A novelty route for smartphone-based artificial intelligence approach to ophthalmic screening.
Journal of the Chinese Medical Association : JCMA
Oct 1, 2020
Artificial intelligence (AI) has been widely applied in the medical field and achieved enormous milestones in helping specialists to make diagnosis and remedy decisions, particularly in the field of eye diseases and ophthalmic screening. With the dev...
Controversies in artificial intelligence.
Current opinion in ophthalmology
Sep 1, 2020
PURPOSE OF REVIEW: To review four recent controversial topics arising from deep learning applications in ophthalmology.
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