Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
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Asia Pac J Ophthalmol (Phila) · Sep 2019
ReviewLow-Concentration Atropine Eye Drops for Myopia Progression.
Atropine eye drops is an emerging therapy for myopia control. This article reviews the recent clinical trials to provide a better understanding of the use of atropine eye drops on myopia progression. ⋯ Low concentration atropine is effective in myopia control. The widespread use of low-concentration atropine, especially in East Asia, may help prevent the myopia progression for the high-risk children. Further investigations on the rebound phenomenon following drops cessation, and longer-term individualized treatment approach should be warranted.
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Asia Pac J Ophthalmol (Phila) · May 2019
ReviewPromising Artificial Intelligence-Machine Learning-Deep Learning Algorithms in Ophthalmology.
The lifestyle of modern society has changed significantly with the emergence of artificial intelligence (AI), machine learning (ML), and deep learning (DL) technologies in recent years. Artificial intelligence is a multidimensional technology with various components such as advanced algorithms, ML and DL. Together, AI, ML, and DL are expected to provide automated devices to ophthalmologists for early diagnosis and timely treatment of ocular disorders in the near future. ⋯ Consequently, given the current population growth trends, it is inevitable that analyzing such images is time-consuming, costly, and prone to human error. Therefore, the detection and treatment of DR, AMD, glaucoma, and other ophthalmic disorders through unmanned automated applications system in the near future will be inevitable. We provide an overview of the potential impact of the current AI, ML, and DL methods and their applications on the early detection and treatment of DR, AMD, glaucoma, and other ophthalmic diseases.
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Asia Pac J Ophthalmol (Phila) · Mar 2019
ReviewArtificial Intelligence and Optical Coherence Tomography Imaging.
This review article aimed to highlight the application and use of artificial intelligence (AI) in optical coherence tomography (OCT) imaging in ophthalmology. Artificial intelligence programs seek to simulate intelligent human behavior in computers. With an abundance of patient data, especially with the advent and growing use of imaging modalities such as OCT, AI programs provide us with the unique opportunity to analyze this plethora of information and assist in making clinical decisions in the field of ophthalmology. ⋯ Incorporation of AI in medicine, however, is not without its pitfalls. Some limitations of AI in ophthalmology are also discussed in this review. These include the deskilling of physicians due to increase in reliance on automation, inability of AI programs to take a holistic approach to clinical encounters with patients, requirement of pre-existing strong datasets to train AI programs, and the inability of AI programs to incorporate the ambiguity and variability that is intrinsic to the nature of clinical medicine.
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Asia Pac J Ophthalmol (Phila) · Nov 2018
Concept and Uptake of Just-A-Minute Clinical Pearl: A Novel Tele-Ophthalmology Teaching Tool.
To describe the concept and report the uptake of a novel tele-ophthalmology educational tool, Just-A-Minute (JAM) clinical pearl, which was sent to all ophthalmologists in the email database of L V Prasad Eye Institute on a daily basis from September 2016 to August 2017. ⋯ In this survey, it was found that the JAM clinical pearls are a unique, beneficial mode of tele-education with easily understandable and clinically applicable concepts.
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Asia Pac J Ophthalmol (Phila) · Nov 2018
ReviewCan Artificial Intelligence Make Screening Faster, More Accurate, and More Accessible?
Diabetic retinopathy, glaucoma, and age-related macular degeneration are leading causes of vision loss and blindness worldwide. They tend to be asymptomatic in the early phase of disease and therefore require active screening programs to identify the patients requiring referral and treatment. ⋯ This paper aimed to provide a general view of the major findings on the application of deep learning for the classification of eye diseases from common imaging modalities. In the future, it is expected that these technologies will be applied in real-world screening programs to improve their efficiency and affordability.