This study explores the potential of Artificial Intelligence (AI) in early screening and
prognosis of Dry Eye Disease (DED), aiming to enhance the accuracy of therapeutic …

Corneal diseases represent a growing public health burden, especially in resource-limited
settings lacking access to specialized eye care. Artificial intelligence (AI) offers promising …

Meibomian gland dysfunction (MGD) is increasingly recognized as a critical contributor to
evaporative dry eye, significantly impacting visual quality. With a global prevalence …

Ophthalmology is a subject that highly depends on imaging examination. Artificial
intelligence (AI) technology has great potential in medical imaging analysis, including image …

Dry eye disease (DED) is one of the most common diseases worldwide that can lead to a
significant impairment of quality of life. The diagnosis and treatment of the disease are often …

The global prevalence of ocular surface diseases (OSDs), such as dry eyes, conjunctivitis,
and subconjunctival hemorrhage (SCH), is steadily increasing due to factors such as aging …

Purpose To use artificial intelligence to identify relationships between morphological
characteristics of the Meibomian glands (MGs), subject factors, clinical outcomes, and …

To develop a deep learning model for automatically segmenting tarsus and meibomian
gland areas on meibography, we included 1087 meibography images from dry eye patients …

Purpose To develop and evaluate a deep learning algorithm for Meibomian gland
characteristics calculation. Design Evaluation of diagnostic technology. Subjects A total of …

Purpose: This study enhances Meibomian gland (MG) infrared image analysis in dry eye
(DE) research through artificial intelligence (AI). It is comprised of two main stages …