AI Medical Compendium Topic

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Tears

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Automated quantification of meibomian gland dropout in infrared meibography using deep learning.

The ocular surface
PURPOSE: Develop a deep learning-based automated method to segment meibomian glands (MG) and eyelids, quantitatively analyze the MG area and MG ratio, estimate the meiboscore, and remove specular reflections from infrared images.

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 ...

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.

Deep learning framework for automated goblet cell density analysis in in-vivo rabbit conjunctiva.

Scientific reports
Goblet cells (GCs) in the conjunctiva are specialized epithelial cells secreting mucins for the mucus layer of protective tear film and playing immune tolerance functions for ocular surface health. Because GC loss is observed in various ocular surfac...

Machine learning-based prediction of tear osmolarity for contact lens practice.

Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)
PURPOSE: This study addressed the utilisation of machine learning techniques to estimate tear osmolarity, a clinically significant yet challenging parameter to measure accurately. Elevated tear osmolarity has been observed in contact lens wearers and...

Automated tear film break-up time measurement for dry eye diagnosis using deep learning.

Scientific reports
In the realm of ophthalmology, precise measurement of tear film break-up time (TBUT) plays a crucial role in diagnosing dry eye disease (DED). This study aims to introduce an automated approach utilizing artificial intelligence (AI) to mitigate subje...

Rapid detection of drug abuse via tear analysis using surface enhanced Raman spectroscopy and machine learning.

Scientific reports
With the growing global challenge of drug abuse, there is an urgent need for rapid, accurate, and cost-effective drug detection methods. This study introduces an innovative approach to drug abuse screening by quickly detecting ephedrine (EPH) in tear...

[Vigorously advancing the application of AI in the diagnosis and treatment of ocular surface and tear diseases].

[Zhonghua yan ke za zhi] Chinese journal of ophthalmology
Ocular surface and tear diseases are among the most common and significant ocular conditions affecting eye health. In recent years, research and clinical diagnosis and treatment of ocular surface and tear diseases have rapidly developed in China, but...