AIMC Topic: Photography
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Performance of deep learning for detection of chronic kidney disease from retinal fundus photographs: A systematic review and meta-analysis.
European journal of ophthalmology
Sep 6, 2023
OBJECTIVE: Deep learning has been used to detect chronic kidney disease (CKD) from retinal fundus photographs. We aim to evaluate the performance of deep learning for CKD detection.
Diabetic Retinopathy Screening Using Smartphone-Based Fundus Photography and Deep-Learning Artificial Intelligence in the Yucatan Peninsula: A Field Study.
Journal of diabetes science and technology
Aug 29, 2023
BACKGROUND: To compare the performance of Medios (offline) and EyeArt (online) artificial intelligence (AI) algorithms for detecting diabetic retinopathy (DR) on images captured using fundus-on-smartphone photography in a remote outreach field settin...
Deep Learning Model to Classify and Monitor Idiopathic Scoliosis in Adolescents Using a Single Smartphone Photograph.
JAMA network open
Aug 1, 2023
IMPORTANCE: Adolescent idiopathic scoliosis (AIS) is the most common pediatric spinal disorder. Routine physical examinations by trained personnel are critical to diagnose severity and monitor curve progression in AIS. In the presence of concerning m...
Detecting dental caries on oral photographs using artificial intelligence: A systematic review.
Oral diseases
Jul 1, 2023
OBJECTIVES: This systematic review aimed at evaluating the performance of artificial intelligence (AI) models in detecting dental caries on oral photographs.
Cross-camera Performance of Deep Learning Algorithms to Diagnose Common Ophthalmic Diseases: A Comparative Study Highlighting Feasibility to Portable Fundus Camera Use.
Current eye research
May 29, 2023
PURPOSE: To compare the inter-camera performance and consistency of various deep learning (DL) diagnostic algorithms applied to fundus images taken from desktop Topcon and portable Optain cameras.
Understanding the Impact of Aging on Attractiveness Using a Machine Learning Model of Facial Age Progression.
Facial plastic surgery & aesthetic medicine
Apr 12, 2023
Advances in machine learning age progression technology offer the unique opportunity to better understand the public's perception on the aging face. To compare how observers perceive attractiveness and traditional gender traits in faces created wit...
Deep Learning-based Prediction of Axial Length Using Ultra-widefield Fundus Photography.
Korean journal of ophthalmology : KJO
Feb 9, 2023
PURPOSE: To develop a deep learning model that can predict the axial lengths of eyes using ultra-widefield (UWF) fundus photography.
Using deep learning to detect diabetic retinopathy on handheld non-mydriatic retinal images acquired by field workers in community settings.
Scientific reports
Jan 25, 2023
Diabetic retinopathy (DR) at risk of vision loss (referable DR) needs to be identified by retinal screening and referred to an ophthalmologist. Existing automated algorithms have mostly been developed from images acquired with high cost mydriatic ret...
Combining convolutional neural networks and self-attention for fundus diseases identification.
Scientific reports
Jan 2, 2023
Early detection of lesions is of great significance for treating fundus diseases. Fundus photography is an effective and convenient screening technique by which common fundus diseases can be detected. In this study, we use color fundus images to dist...
Monitoring and Identification of Road Construction Safety Factors via UAV.
Sensors (Basel, Switzerland)
Nov 14, 2022
The safety of road construction is one of the most important concerns of construction managers for the following reasons: long-span construction operation, no fixed monitoring cameras, and huge impacts on existing traffic, while the managers still re...
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