AIMC Topic: Dry Eye Syndromes
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Artificial intelligence models utilize lifestyle factors to predict dry eye related outcomes.
Scientific reports
Apr 18, 2025
The purpose of this study is to examine and interpret machine learning models that predict dry eye (DE)-related clinical signs, subjective symptoms, and clinician diagnoses by heavily weighting lifestyle factors in the predictions. Machine learning m...
Deep-learning based analysis of in-vivo confocal microscopy images of the subbasal corneal nerve plexus' inferior whorl in patients with neuropathic corneal pain and dry eye disease.
The ocular surface
Aug 2, 2024
PURPOSE: To evaluate and compare subbasal corneal nerve parameters of the inferior whorl in patients with dry eye disease (DED), neuropathic corneal pain (NCP), and controls using a novel deep-learning-based algorithm to analyze in-vivo confocal micr...
Applications of Artificial Intelligence in Diagnosis of Dry Eye Disease: A Systematic Review and Meta-Analysis.
Cornea
Jul 9, 2024
PURPOSE: Clinical diagnosis of dry eye disease is based on a subjective Ocular Surface Disease Index questionnaire or various objective tests, however, these diagnostic methods have several limitations.
Automated tear film break-up time measurement for dry eye diagnosis using deep learning.
Scientific reports
May 22, 2024
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...
Eye-LRCN: A Long-Term Recurrent Convolutional Network for Eye Blink Completeness Detection.
IEEE transactions on neural networks and learning systems
Apr 4, 2024
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...
Machine learning-based prediction of tear osmolarity for contact lens practice.
Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)
Mar 25, 2024
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...
Deep learning-based fully automated grading system for dry eye disease severity.
PloS one
Mar 14, 2024
There is an increasing need for an objective grading system to evaluate the severity of dry eye disease (DED). In this study, a fully automated deep learning-based system for the assessment of DED severity was developed. Corneal fluorescein staining ...
Automated identification and quantification of activated dendritic cells in central cornea using artificial intelligence.
The ocular surface
Jun 27, 2023
PURPOSE: To validate an algorithm quantifying activated dendritic cells (aDCs) using in-vivo confocal microscopy (IVCM) images.
ChatGPT as a tool for conducting literature review for dry eye disease.
Clinical & experimental ophthalmology
Jun 15, 2023
Artificial intelligence to estimate the tear film breakup time and diagnose dry eye disease.
Scientific reports
Apr 10, 2023
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...
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