AIMC Topic: Tears

Clear Filters Showing 1 to 10 of 20 articles

Exploring biomarkers for keratoconus: current insights and future directions.

Molecular biology reports
Keratoconus (KC) is a progressive corneal disorder characterized by thinning of the cornea and conical protrusion leading to distorted vision and blindness. The disease often marks in adolescence and progresses until the mid-40s, with varying degrees...

Non-invasive detection of choroidal melanoma via tear-derived protein corona on gold nanoparticles: a machine learning approach.

Scientific reports
This study investigates the feasibility of using tear sample analysis, based on protein corona formation on gold nanoparticles combined with electrospray ionization mass spectrometry (ESI-MS) and machine learning techniques, as a non-invasive approac...

Determination of miRNA in tear extracellular vesicles significantly associated with treatment-requiring retinopathy of prematurity: a pilot study.

Scientific reports
Retinopathy of prematurity (ROP) develops in some premature infants and may be characterized by permanent severe retinal damage necessitating early detection and prompt treatment. The purpose of this study was to investigate whether specific miRNAs i...

Performance of a novel multimodal large language model in ınterpreting meibomian glands quantitatively and qualitatively.

International ophthalmology
PURPOSE: To evaluate the performance of a multimodal large language model (LLM), Claude 3.5 Sonnet, in interpreting meibography images for Meibomian gland dropout grading and morphological abnormality detection.

Novel protocol for metabolomics data normalization and biomarker discovery in human tears.

Clinical chemistry and laboratory medicine
OBJECTIVES: Human tear analysis holds promise for biomarker discovery, but its clinical utility is hindered by the lack of standardized reference values, limiting interindividual comparisons. This study aimed at developing a protocol for normalizing ...

Rapid detection of drug abuse via tear analysis using surface enhanced Raman spectroscopy and machine learning.

Scientific reports
With the growing global challenge of drug abuse, there is an urgent need for rapid, accurate, and cost-effective drug detection methods. This study introduces an innovative approach to drug abuse screening by quickly detecting ephedrine (EPH) in tear...

Automated tear film break-up time measurement for dry eye diagnosis using deep learning.

Scientific reports
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...

Machine learning-based prediction of tear osmolarity for contact lens practice.

Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)
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 framework for automated goblet cell density analysis in in-vivo rabbit conjunctiva.

Scientific reports
Goblet cells (GCs) in the conjunctiva are specialized epithelial cells secreting mucins for the mucus layer of protective tear film and playing immune tolerance functions for ocular surface health. Because GC loss is observed in various ocular surfac...

Artificial intelligence to estimate the tear film breakup time and diagnose dry eye disease.

Scientific reports
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...