AI Medical Compendium Topic

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Tears

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S100 proteins, cytokines, and chemokines as tear biomarkers in children with juvenile idiopathic arthritis-associated uveitis.

Ocular immunology and inflammation
PURPOSE: Biomarkers for juvenile idiopathic arthritis-associated uveitis (JIA-U) are needed. We aimed to measure inflammatory biomarkers in tears as a non-invasive method to identify biomarkers of uveitis activity.

Characterization of expressed human meibum using hyperspectral stimulated Raman scattering microscopy.

The ocular surface
PURPOSE: This study examined whether hyperspectral stimulated Raman scattering (hsSRS) microscopy can detect differences in meibum lipid to protein composition of normal and evaporative dry eye subjects with meibomian gland dysfunction.

Dry eye is matched by increased intrasubject variability in tear osmolarity as confirmed by machine learning approach.

Archivos de la Sociedad Espanola de Oftalmologia
OBJECTIVE: Because of high variability, tear film osmolarity measures have been questioned in dry eye assessment. Understanding the origin of such variability would aid data interpretation. This study aims to evaluate osmolarity variability in a clin...

Automatic screening of tear meniscus from lacrimal duct obstructions using anterior segment optical coherence tomography images by deep learning.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: We assessed the ability of deep learning (DL) models to distinguish between tear meniscus of lacrimal duct obstruction (LDO) patients and normal subjects using anterior segment optical coherence tomography (ASOCT) images.

Impact of Incomplete Blinking Analyzed Using a Deep Learning Model With the Keratograph 5M in Dry Eye Disease.

Translational vision science & technology
PURPOSE: To establish a deep learning model (DLM) for blink analysis, and investigate whether blink video frame sampling rate influences the accuracy of analysis.