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Keratitis

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Accuracy of artificial intelligence model for infectious keratitis classification: a systematic review and meta-analysis.

Frontiers in public health
BACKGROUND: Infectious keratitis (IK) is a sight-threatening condition requiring immediate definite treatment. The need for prompt treatment heavily depends on timely diagnosis. The diagnosis of IK, however, is challenged by the drawbacks of the curr...

Determination of probability of causative pathogen in infectious keratitis using deep learning algorithm of slit-lamp images.

Scientific reports
Corneal opacities are important causes of blindness, and their major etiology is infectious keratitis. Slit-lamp examinations are commonly used to determine the causative pathogen; however, their diagnostic accuracy is low even for experienced ophtha...

Deep Convolutional Neural Networks Detect no Morphological Differences Between Culture-Positive and Culture-Negative Infectious Keratitis Images.

Translational vision science & technology
PURPOSE: To determine whether convolutional neural networks can detect morphological differences between images of microbiologically positive and negative corneal ulcers.

Diagnostic performance of deep learning in infectious keratitis: a systematic review and meta-analysis protocol.

BMJ open
INTRODUCTION: Infectious keratitis (IK) represents the fifth-leading cause of blindness worldwide. A delay in diagnosis is often a major factor in progression to irreversible visual impairment and/or blindness from IK. The diagnostic challenge is fur...

From the diagnosis of infectious keratitis to discriminating fungal subtypes; a deep learning-based study.

Scientific reports
Infectious keratitis (IK) is a major cause of corneal opacity. IK can be caused by a variety of microorganisms. Typically, fungal ulcers carry the worst prognosis. Fungal cases can be subdivided into filamentous and yeasts, which shows fundamental di...

Application of Deep Learning Algorithms Based on the Multilayer Y0L0v8 Neural Network to Identify Fungal Keratitis.

Sovremennye tekhnologii v meditsine
UNLABELLED: is to develop a method for diagnosing fungal keratitis based on the analysis of photographs of the anterior segment of the eye using deep learning algorithms with subsequent evaluation of sensitivity and specificity of the method on a te...

Evaluating the accuracy of the Ophthalmologist Robot for multiple blindness-causing eye diseases: a multicentre, prospective study protocol.

BMJ open
INTRODUCTION: Early eye screening and treatment can reduce the incidence of blindness by detecting and addressing eye diseases at an early stage. The Ophthalmologist Robot is an automated device that can simultaneously capture ocular surface and fund...

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...

Promoting smartphone-based keratitis screening using meta-learning: A multicenter study.

Journal of biomedical informatics
OBJECTIVE: Keratitis is the primary cause of corneal blindness worldwide. Prompt identification and referral of patients with keratitis are fundamental measures to improve patient prognosis. Although deep learning can assist ophthalmologists in autom...

Deep learning by Vision Transformer to classify bacterial and fungal keratitis using different types of anterior segment images.

Computers in biology and medicine
PURPOSE: To develop three novel Vision Transformer (ViT) frameworks for the specific diagnosis of bacterial and fungal keratitis using different types of anterior segment images and compare their performances.