AI Medical Compendium Topic

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Dry Eye Syndromes

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[Infrared Imaging Meibomian Gland Segmentation System Based on Deep Learning].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
In order to better assist doctors in the diagnosis of dry eye and improve the ability of ophthalmologists to recognize the condition of meibomian gland, a meibomian gland image segmentation and enhancement method based on Mobile-U-Net network was pro...

Automatic identification of meibomian gland dysfunction with meibography images using deep learning.

International ophthalmology
BACKGROUND: Artificial intelligence is developing rapidly, bringing increasing numbers of intelligent products into daily life. However, it has little progress in dry eye, which is a common disease and associated with meibomian gland dysfunction (MGD...

Current uses of artificial intelligence in the analysis of biofluid markers involved in corneal and ocular surface diseases: a systematic review.

Eye (London, England)
Corneal and ocular surface diseases (OSDs) carry significant psychosocial and economic burden worldwide. We set out to review the literature on the application of artificial intelligence (AI) and bioinformatics for analysis of biofluid biomarkers in ...

Detecting dry eye from ocular surface videos based on deep learning.

The ocular surface
OBJECTIVE: To assess the performance of convolutional neural networks (CNNs) for automated diagnosis of dry eye (DE) in patients undergoing video keratoscopy based on single ocular surface video frames.

Artificial intelligence to estimate the tear film breakup time and diagnose dry eye disease.

Scientific reports
The use of artificial intelligence (AI) in the diagnosis of dry eye disease (DED) remains limited due to the lack of standardized image formats and analysis models. To overcome these issues, we used the Smart Eye Camera (SEC), a video-recordable slit...

Unsupervised Learning Based on Meibography Enables Subtyping of Dry Eye Disease and Reveals Ocular Surface Features.

Investigative ophthalmology & visual science
PURPOSE: This study aimed to establish an image-based classification that can reveal the clinical characteristics of patients with dry eye using unsupervised learning methods.

Visual analysis of autoimmune dry eye studies based on bibliometrics.

Medicine
BACKGROUND: Dry eye is a chronic ocular surface disease caused by the instability of tear film or the imbalance of the ocular surface microenvironment which can lead to a diverse range of ocular discomfort symptoms. At present, the relevant mechanism...

Eye-LRCN: A Long-Term Recurrent Convolutional Network for Eye Blink Completeness Detection.

IEEE transactions on neural networks and learning systems
Computer vision syndrome causes vision problems and discomfort mainly due to dry eye. Several studies show that dry eye in computer users is caused by a reduction in the blink rate and an increase in the prevalence of incomplete blinks. In this conte...