AI Medical Compendium Journal:
Current opinion in ophthalmology

Showing 21 to 30 of 46 articles

Artificial intelligence and ophthalmic surgery.

Current opinion in ophthalmology
PURPOSE OF REVIEW: Artificial intelligence and deep learning have become important tools in extracting data from ophthalmic surgery to evaluate, teach, and aid the surgeon in all phases of surgical management. The purpose of this review is to highlig...

Generative adversarial networks in ophthalmology: what are these and how can they be used?

Current opinion in ophthalmology
PURPOSE OF REVIEW: The development of deep learning (DL) systems requires a large amount of data, which may be limited by costs, protection of patient information and low prevalence of some conditions. Recent developments in artificial intelligence t...

Deep learning-based natural language processing in ophthalmology: applications, challenges and future directions.

Current opinion in ophthalmology
PURPOSE OF REVIEW: Artificial intelligence (AI) is the fourth industrial revolution in mankind's history. Natural language processing (NLP) is a type of AI that transforms human language, to one that computers can interpret and process. NLP is still ...

Artificial intelligence in myopia: current and future trends.

Current opinion in ophthalmology
PURPOSE OF REVIEW: Myopia is one of the leading causes of visual impairment, with a projected increase in prevalence globally. One potential approach to address myopia and its complications is early detection and treatment. However, current healthcar...

Clinician-driven artificial intelligence in ophthalmology: resources enabling democratization.

Current opinion in ophthalmology
PURPOSE OF REVIEW: This article aims to discuss the current state of resources enabling the democratization of artificial intelligence (AI) in ophthalmology.

Artificial intelligence-based predictions in neovascular age-related macular degeneration.

Current opinion in ophthalmology
PURPOSE OF REVIEW: Predicting treatment response and optimizing treatment regimen in patients with neovascular age-related macular degeneration (nAMD) remains challenging. Artificial intelligence-based tools have the potential to increase confidence ...

Gaps in standards for integrating artificial intelligence technologies into ophthalmic practice.

Current opinion in ophthalmology
PURPOSE OF REVIEW: The purpose of this review is to provide an overview of healthcare standards and their relevance to multiple ophthalmic workflows, with a specific emphasis on describing gaps in standards development needed for improved integration...

Applications of interpretability in deep learning models for ophthalmology.

Current opinion in ophthalmology
PURPOSE OF REVIEW: In this article, we introduce the concept of model interpretability, review its applications in deep learning models for clinical ophthalmology, and discuss its role in the integration of artificial intelligence in healthcare.

Automated deep learning in ophthalmology: AI that can build AI.

Current opinion in ophthalmology
PURPOSE OF REVIEW: The purpose of this review is to describe the current status of automated deep learning in healthcare and to explore and detail the development of these models using commercially available platforms. We highlight key studies demons...

Artificial intelligence and complex statistical modeling in glaucoma diagnosis and management.

Current opinion in ophthalmology
PURPOSE OF REVIEW: The field of artificial intelligence has grown exponentially in recent years with new technology, methods, and applications emerging at a rapid rate. Many of these advancements have been used to improve the diagnosis and management...