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Eye Diseases

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An Artificial Intelligence Driven Approach for Classification of Ophthalmic Images using Convolutional Neural Network: An Experimental Study.

Current medical imaging
BACKGROUND: Early disease detection is emphasized within ophthalmology now more than ever, and as a result, clinicians and innovators turn to deep learning to expedite accurate diagnosis and mitigate treatment delay. Efforts concentrate on the creati...

Artificial Intelligence-based database for prediction of protein structure and their alterations in ocular diseases.

Database : the journal of biological databases and curation
The aim of the study is to establish an online database for predicting protein structures altered in ocular diseases by Alphafold2 and RoseTTAFold algorithms. Totally, 726 genes of multiple ocular diseases were collected for protein structure predict...

Modelling and Development of a Mechanical Eye for the Evaluation of Robotic Systems for Surgery.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Ophthalmic surgery, which addresses critical eye diseases such as retinal disorders, remains a formidable and arduous surgical pursuit. Nevertheless, with the advent of cutting-edge robotics and automation technology, significant advancement has been...

[Challenges of artificial intelligence used for eye disease screening in recent China communities].

[Zhonghua yan ke za zhi] Chinese journal of ophthalmology
Due to factors such as medical resources, public awareness, funding for general screening, or optimized screening models, community-based screening is far from meeting the demand. Artificial intelligence (AI) can replace some of the medical work and ...

A Multicenter Clinical Study of the Automated Fundus Screening Algorithm.

Translational vision science & technology
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
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
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
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)
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...