AIMC Topic:
Cross-Sectional Studies
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Fundus Tessellated Density Assessed by Deep Learning in Primary School Children.
Translational vision science & technology
Jun 1, 2023
PURPOSE: To explore associations of fundus tessellated density (FTD) and compare characteristics of different fundus tessellation (FT) distribution patterns, based on artificial intelligence technology using deep learning.
Performance of an Artificial Intelligence Chatbot in Ophthalmic Knowledge Assessment.
JAMA ophthalmology
Jun 1, 2023
IMPORTANCE: ChatGPT is an artificial intelligence (AI) chatbot that has significant societal implications. Training curricula using AI are being developed in medicine, and the performance of chatbots in ophthalmology has not been characterized.
Estimation of Visual Function Using Deep Learning From Ultra-Widefield Fundus Images of Eyes With Retinitis Pigmentosa.
JAMA ophthalmology
Apr 1, 2023
IMPORTANCE: There is no widespread effective treatment to halt the progression of retinitis pigmentosa. Consequently, adequate assessment and estimation of residual visual function are important clinically.
AxoNet 2.0: A Deep Learning-Based Tool for Morphometric Analysis of Retinal Ganglion Cell Axons.
Translational vision science & technology
Mar 1, 2023
PURPOSE: Assessment of glaucomatous damage in animal models is facilitated by rapid and accurate quantification of retinal ganglion cell (RGC) axonal loss and morphologic change. However, manual assessment is extremely time- and labor-intensive. Here...
The Use of Natural Language Processing to Assess Social Support in Patients With Advanced Cancer.
The oncologist
Feb 8, 2023
BACKGROUND: Data examining associations among social support, survival, and healthcare utilization are lacking in patients with advanced cancer.
Real-time detection of acromegaly from facial images with artificial intelligence.
European journal of endocrinology
Jan 10, 2023
OBJECTIVE: Despite improvements in diagnostic methods, acromegaly is still a late-diagnosed disease. In this study, it was aimed to automatically recognize acromegaly disease from facial images by using deep learning methods and to facilitate the det...
Deep Convolutional Neural Networks Detect no Morphological Differences Between Culture-Positive and Culture-Negative Infectious Keratitis Images.
Translational vision science & technology
Jan 3, 2023
PURPOSE: To determine whether convolutional neural networks can detect morphological differences between images of microbiologically positive and negative corneal ulcers.
Development of a Web Application based on Machine Learning for screening esophageal varices in cirrhosis.
La Tunisie medicale
Jan 1, 2023
INTRODUCTION: Esophageal varices (EV) are a common manifestation of portal hypertension in cirrhotic patients. Upper gastrointestinal endoscopy (UGE) is the gold standard for diagnosing EV. However, it is an invasive examination with a relatively hig...
Exploring artificial intelligence in the Nigerian medical educational space: An online cross-sectional study of perceptions, risks and benefits among students and lecturers from ten universities.
The Nigerian postgraduate medical journal
Jan 1, 2023
BACKGROUND: The impact of artificial intelligence (AI) has been compared to that of the Internet and printing, evoking both apprehension and anticipation in an uncertain world.
Enhanced Diagnosis of Plaque Erosion by Deep Learning in Patients With Acute Coronary Syndromes.
JACC. Cardiovascular interventions
Oct 24, 2022
BACKGROUND: Acute coronary syndromes caused by plaque erosion might be potentially managed conservatively without stenting. Currently, the diagnosis of plaque erosion requires expertise in optical coherence tomographic (OCT) image interpretation. In ...
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