AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Cornea

Showing 21 to 30 of 89 articles

Clear Filters

Taxonomy, biological characterization and fungicide sensitivity assays of Hypomyces cornea sp. nov. causing cobweb disease on Auricularia cornea.

Fungal biology
Auricularia cornea is an important edible mushroom crop in China but the occurrence of cobweb disease has cause significance economic loss in its production. The rate of disease occurrence is 16.65% all over the country. In the present study, a new p...

Precise localization of corneal reflections in eye images using deep learning trained on synthetic data.

Behavior research methods
We present a deep learning method for accurately localizing the center of a single corneal reflection (CR) in an eye image. Unlike previous approaches, we use a convolutional neural network (CNN) that was trained solely using synthetic data. Using on...

Deep learning-based fully automated grading system for dry eye disease severity.

PloS one
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 ...

Performance of ChatGPT in Diagnosis of Corneal Eye Diseases.

Cornea
PURPOSE: The aim of this study was to assess the capabilities of ChatGPT-4.0 and ChatGPT-3.5 for diagnosing corneal eye diseases based on case reports and compare with human experts.

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
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...

Automated Measurement and Three-Dimensional Fitting of Corneal Ulcerations and Erosions via AI-Based Image Analysis.

Current eye research
PURPOSE: Artificial intelligence (AI)-tools hold great potential to compensate for missing resources in health-care systems but often fail to be implemented in clinical routine. Intriguingly, no-code and low-code technologies allow clinicians to deve...

Ocular Biometric Components in Hyperopic Children and a Machine Learning-Based Model to Predict Axial Length.

Translational vision science & technology
PURPOSE: The purpose of this study was to investigate the development of optical biometric components in children with hyperopia, and apply a machine-learning model to predict axial length.

Keratoconus Progression Determined at the First Visit: A Deep Learning Approach With Fusion of Imaging and Numerical Clinical Data.

Translational vision science & technology
PURPOSE: Multiple clinical visits are necessary to determine progression of keratoconus before offering corneal cross-linking. The purpose of this study was to develop a neural network that can potentially predict progression during the initial visit...

An AS-OCT image dataset for deep learning-enabled segmentation and 3D reconstruction for keratitis.

Scientific data
Infectious keratitis is among the major causes of global blindness. Anterior segment optical coherence tomography (AS-OCT) images allow the characterizing of cross-sectional structures in the cornea with keratitis thus revealing the severity of infla...