The aim of this study was to determine the relative effects of age and compromised vision on driving-related skills and on-road accidents. A total of 107 subjects were tested. They represented four groups that varied in age and visual status, as follows: (1) a younger, normally sighted group; (2) an older, normally sighted group; (3) a younger, visually compromised group; and (4) an older, visually compromised group. Driving performance was assessed by self-reported and state-recorded accident frequency and by an evaluation of performance on an interactive driving simulator. The older groups had poorer driving-related skills, as measured with our interactive driving simulator, than had the younger groups, but they did not have significantly higher on-road accident rates than the younger groups. The older subjects and those with compromised vision had reduced risk-taking scores, as measured with a self-report questionnaire. In addition, all older drivers had increased eye movements and had slower simulator driving speeds, which suggests that behavioral compensation is made for visuocognitive/motor deficits. Regression analyses showed that compromised vision and visual field loss predicted real-world accidents in our study population.
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http://dx.doi.org/10.1518/001872095779064645 | DOI Listing |
Cureus
December 2024
Department of Orthodontics, School of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, IRN.
Background Orthodontic diagnostic workflows often rely on manual classification and archiving of large volumes of patient images, a process that is both time-consuming and prone to errors such as mislabeling and incomplete documentation. These challenges can compromise treatment accuracy and overall patient care. To address these issues, we propose an artificial intelligence (AI)-driven deep learning framework based on convolutional neural networks (CNNs) to automate the classification and archiving of orthodontic diagnostic images.
View Article and Find Full Text PDFJ Am Soc Nephrol
January 2025
Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Background: Deficiency of adiponectin and its downstream signaling may contribute to the pathogenesis of kidney injury in type 2 diabetes. Adiponectin activates intracellular signaling via adiponectin receptors 1 and 2 (AdipoR1 and AdipoR2), but the role of AdipoR-mediated signaling in glomerular injury in type 2 diabetes remains unknown.
Methods: The expression of AdipoR1 in the kidneys of people with type 2 diabetes and the expression of podocyte proteins or injury markers in the kidneys of AdipoR1-knockout (AdipoR1-KO) mice and immortalized AdipoR1-deficient human podocytes were investigated by immunohistochemistry and immunoblotting.
Transl Vis Sci Technol
January 2025
Department of Biomedical Engineering, Faculty of Engineering, Mahidol University, Nakhon Pathom, Thailand.
Purpose: The purpose of this study was to develop a deep learning approach that restores artifact-laden optical coherence tomography (OCT) scans and predicts functional loss on the 24-2 Humphrey Visual Field (HVF) test.
Methods: This cross-sectional, retrospective study used 1674 visual field (VF)-OCT pairs from 951 eyes for training and 429 pairs from 345 eyes for testing. Peripapillary retinal nerve fiber layer (RNFL) thickness map artifacts were corrected using a generative diffusion model.
Front Robot AI
January 2025
CREATE Lab, Institute of Mechanical Engineering, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Laboratory automation requires reliable and precise handling of microplates, but existing robotic systems often struggle to achieve this, particularly when navigating around the dynamic and variable nature of laboratory environments. This work introduces a novel method integrating simultaneous localization and mapping (SLAM), computer vision, and tactile feedback for the precise and autonomous placement of microplates. Implemented on a bi-manual mobile robot, the method achieves fine-positioning accuracies of 1.
View Article and Find Full Text PDFVision Res
January 2025
Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brazil.
Elevated intraocular pressure (IOP) is a significant risk factor for glaucoma, causing structural and functional damage to the eye. Increased IOP compromises the metabolic and structural integrity of retinal ganglion cell (RGC) axons, leading to progressive degeneration and influencing the ocular immune response. This study investigated early cellular and molecular changes in the retina and optic nerve (ON) following ocular hypertension (OHT).
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