Results 71 to 80 of about 1,758 (162)
Temporal variations in meibomian gland structure—A pilot study
Ophthalmic and Physiological Optics, Volume 44, Issue 5, Page 894-909, July 2024.Abstract Purpose To investigate whether there is a measurable change in meibomian gland morphological characteristics over the course of a day (12 h) and over a month. Methods The study enrolled 15 participants who attended a total of 11 study visits spanning a 5‐week period. To assess diurnal changes in meibomian glands, seven visits were conducted on
Kasandra Swiderska +5 more
wiley +1 more source
Methods of Screening for Meibomian Gland Dysfunction
Oftalʹmologiâ, 2016 The relevance of the modern diagnosis of meibomian glands dysfunction (MGD) increases daily. Firstly, it is caused by changing of the perception about the prevalence of this disease, according to various data it is from 40 to 71% of the population in ...
V. N. Trubilin +5 more
doaj +1 more source
Intense pulsed light treatment in meibomian gland dysfunction: Past, present, and future
Acta Ophthalmologica, Volume 102, Issue 4, Page e414-e442, June 2024.Abstract Dry eye disease is a highly prevalent condition, which can substantially impair quality of life, work productivity, and vision. It is considered an inflammatory disease and the most common cause is meibomian gland dysfunction. Despite many treatment alternatives being available, including artificial tears, warm compresses, antibiotics, and ...
Fredrik Fineide +5 more
wiley +1 more source
Machine learning‐based prediction of tear osmolarity for contact lens practice
Ophthalmic and Physiological Optics, Volume 44, Issue 4, Page 727-736, June 2024.Abstract 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 is associated with contact lens‐induced dry eye, a common cause of discomfort leading to ...
Izabela K. Garaszczuk +2 more
wiley +1 more source
Evaluation of Dry Eye and Meibomian Gland Dysfunction With Meibography in Patients With Rosacea
, 2015 Purpose: To evaluate the dry eye tests and meibography of patients with ocular rosacea. Methods: Thirty-six eyes of 18 patients with ocular rosacea (group 1) and 38 eyes of 19 healthy individuals (group 2) were enrolled.
Palamar, Melis +3 more
core +1 more source
Novel Application Software for the Semi-Automated Analysis of Infrared Meibography Images [PDF]
, 2019 Purpose: To develop semi-automated application software that quickly analyzes infrared meibography images taken with the CSO Sirius Topographer (CSO, Italy) and to compare them to the manual analysis system on the device (Phoenix software platform ...
Banu Bozkurt +7 more
core +1 more source
, 2023 This cross-sectional study supports the feasibility of screening for dry eye disease through symptom questionnaires and automated meibography.
Marco Pellegrini +7 more
core +1 more source
Meibomian gland function cannot be predicted by Meibography in patients symptomatic for dry eye
, 2014 Purpose: The purpose of this study was to determine if meibography could predict meibomian gland (MG) function with regard to number of functional MGs and/or estimation of functional MG volume in patients symptomatic for dry eye. Methods: Patients (n=23)
Murakami, David +3 more
core +3 more sources
Meibomian Gland Loss and Dysfunction in Mild versus Moderate-Severe Thyroid Eye Disease
Journal of Current OphthalmologyPurpose: To compare meibomian gland (MG) loss and MG dysfunction (MGD) in patients with mild versus moderate-severe thyroid eye disease (TED). Methods: Consecutive patients with TED and no other causes of dry eye disease underwent meibography and ...
Hossein Aghaei +8 more
doaj +1 more source
Utility of artificial intelligence‐based large language models in ophthalmic care
Ophthalmic and Physiological Optics, Volume 44, Issue 3, Page 641-671, May 2024.Abstract Purpose With the introduction of ChatGPT, artificial intelligence (AI)‐based large language models (LLMs) are rapidly becoming popular within the scientific community. They use natural language processing to generate human‐like responses to queries.
Sayantan Biswas +4 more
wiley +1 more source