AIMC Topic: 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
May 28, 2020
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.
Dry eye is matched by increased intrasubject variability in tear osmolarity as confirmed by machine learning approach.
Archivos de la Sociedad Espanola de Oftalmologia
May 20, 2019
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...
Characterization of expressed human meibum using hyperspectral stimulated Raman scattering microscopy.
The ocular surface
Oct 11, 2018
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.
[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
Feb 14, 2025
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...
Unsupervised Learning Based on Meibography Enables Subtyping of Dry Eye Disease and Reveals Ocular Surface Features.
Investigative ophthalmology & visual science
Oct 3, 2023
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.
Impact of Incomplete Blinking Analyzed Using a Deep Learning Model With the Keratograph 5M in Dry Eye Disease.
Translational vision science & technology
Mar 2, 2022
PURPOSE: To establish a deep learning model (DLM) for blink analysis, and investigate whether blink video frame sampling rate influences the accuracy of analysis.
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