AIMC Topic: Conjunctiva
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Computer Vision Identification of Trachomatous Inflammation-Follicular Using Deep Learning.
Cornea
Sep 20, 2024
PURPOSE: Trachoma surveys are used to estimate the prevalence of trachomatous inflammation-follicular (TF) to guide mass antibiotic distribution. These surveys currently rely on human graders, introducing a significant resource burden and potential f...
Machine/deep learning-assisted hemoglobin level prediction using palpebral conjunctival images.
British journal of haematology
Jul 18, 2024
Palpebral conjunctival hue alteration is used in non-invasive screening for anaemia, whereas it is a qualitative measure. This study constructed machine/deep learning models for predicting haemoglobin values using 150 palpebral conjunctival images ta...
Assessing the proficiency of artificial intelligence programs in the diagnosis and treatment of cornea, conjunctiva, and eyelid diseases and exploring the advantages of each other benefits.
Contact lens & anterior eye : the journal of the British Contact Lens Association
Mar 4, 2024
PURPOSE: It was aimed to determine the knowledge level of ChatGPT, Bing, and Bard artificial intelligence programs related to corneal, conjunctival, and eyelid diseases and treatment modalities, to examine their reliability and superiority to each ot...
Deep learning framework for automated goblet cell density analysis in in-vivo rabbit conjunctiva.
Scientific reports
Dec 21, 2023
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...
Non-invasive hemoglobin estimation from conjunctival images using deep learning.
Medical engineering & physics
Aug 22, 2023
Hemoglobin, a crucial protein found in erythrocytes, transports oxygen throughout the body. Deviations from optimal hemoglobin levels in the blood are linked to medical conditions, serving as diagnostic markers for certain diseases. The hemoglobin le...
Pterygium Screening and Lesion Area Segmentation Based on Deep Learning.
Journal of healthcare engineering
Nov 21, 2022
A two-category model and a segmentation model of pterygium were proposed to assist ophthalmologists in establishing the diagnosis of ophthalmic diseases. A total of 367 normal anterior segment images and 367 pterygium anterior segment images were col...
Quantification of Blood Flow Velocity in the Human Conjunctival Microvessels Using Deep Learning-Based Stabilization Algorithm.
Sensors (Basel, Switzerland)
May 6, 2021
The quantification of blood flow velocity in the human conjunctiva is clinically essential for assessing microvascular hemodynamics. Since the conjunctival microvessel is imaged in several seconds, eye motion during image acquisition causes motion ar...
Sensitivity and specificity of computer vision classification of eyelid photographs for programmatic trachoma assessment.
PloS one
Feb 11, 2019
BACKGROUND/AIMS: Trachoma programs base treatment decisions on the community prevalence of the clinical signs of trachoma, assessed by direct examination of the conjunctiva. Automated assessment could be more standardized and more cost-effective. We ...
Machine learning of blood haemoglobin and haematocrit levels via smartphone conjunctiva photography in Kenyan pregnant women: a clinical study protocol.
BMJ open
May 8, 2025
INTRODUCTION: Anaemia during pregnancy is a widespread health burden globally, especially in low- and middle-income countries, posing a serious risk to both maternal and neonatal health. The primary challenge is that anaemia is frequently undetected ...
Examining different cost ratio frameworks for decision rule machine learning algorithms in diagnostic application.
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2024
BACKGROUND: Artificial Intelligence (AI) plays a pivotal role in the diagnosis of health conditions ranging from general well-being to critical health issues. In the realm of health diagnostics, an often overlooked but critical aspect is the consider...
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