AIMC Topic: Young Adult
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Impact of training data composition on the generalizability of convolutional neural network aortic cross-section segmentation in four-dimensional magnetic resonance flow imaging.
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Aug 8, 2024
BACKGROUND: Four-dimensional cardiovascular magnetic resonance flow imaging (4D flow CMR) plays an important role in assessing cardiovascular diseases. However, the manual or semi-automatic segmentation of aortic vessel boundaries in 4D flow data int...
Perfusion Imaging
Bicuspid Aortic Valve Disease
Datasets as Topic
Blood Flow Velocity
Middle Aged
Aorta
Case-Control Studies
Hemodynamics
Deep Learning
Aortic Valve
Predictive Value of Tests
Humans
Regional Blood Flow
Neural Networks, Computer
Image Interpretation, Computer-Assisted
Female
Reproducibility of Results
Aged
Young Adult
Adult
Male
Human-Robot Collaboration With a Corrective Shared Controlled Robot in a Sanding Task.
Human factors
Aug 8, 2024
OBJECTIVE: Physical and cognitive workloads and performance were studied for a corrective shared control (CSC) human-robot collaborative (HRC) sanding task.
Deep learning MR reconstruction in knees and ankles in children and young adults. Is it ready for clinical use?
Skeletal radiology
Aug 8, 2024
OBJECTIVE: To evaluate the diagnostic performance and image quality of accelerated Turbo Spin Echo sequences using deep-learning (DL) reconstructions compared to conventional sequences in knee and ankle MRIs of children and young adults.
Automated 3D Cobb Angle Measurement Using U-Net in CT Images of Preoperative Scoliosis Patients.
Journal of imaging informatics in medicine
Aug 8, 2024
To propose a deep learning framework "SpineCurve-net" for automated measuring the 3D Cobb angles from computed tomography (CT) images of presurgical scoliosis patients. A total of 116 scoliosis patients were analyzed, divided into a training set of 8...
Contrastive fine-grained domain adaptation network for EEG-based vigilance estimation.
Neural networks : the official journal of the International Neural Network Society
Aug 8, 2024
Vigilance state is crucial for the effective performance of users in brain-computer interface (BCI) systems. Most vigilance estimation methods rely on a large amount of labeled data to train a satisfactory model for the specific subject, which limits...
Deep learning-based automated angle measurement for flatfoot diagnosis in weight-bearing lateral radiographs.
Scientific reports
Aug 8, 2024
This study aimed to develop and evaluate a deep learning-based system for the automatic measurement of angles (specifically, Meary's angle and calcaneal pitch) in weight-bearing lateral radiographs of the foot for flatfoot diagnosis. We utilized 3960...
Proprioception enhancement for robot assisted neural rehabilitation: a dynamic electrical stimulation based method and preliminary results from EEG analysis.
Journal of neural engineering
Aug 8, 2024
In recent years, the robot assisted (RA) rehabilitation training has been widely used to counteract defects of the manual one provided by physiotherapists. However, since the proprioception feedback provided by the robotic assistance or the manual me...
Convolutional neural networks can identify brain interactions involved in decoding spatial auditory attention.
PLoS computational biology
Aug 8, 2024
Human listeners have the ability to direct their attention to a single speaker in a multi-talker environment. The neural correlates of selective attention can be decoded from a single trial of electroencephalography (EEG) data. In this study, leverag...
Stress Classification and Vital Signs Forecasting for IoT-Health Monitoring.
IEEE/ACM transactions on computational biology and bioinformatics
Aug 8, 2024
Health monitoring embedded with intelligence is the demand of the day. In this era of a large population with the emergence of a variety of diseases, the demand for healthcare facilities is high. Yet there is scarcity of medical experts, technicians ...
Single-Task and Dual-Task Gait Performance After Sport-Related Concussion: A Machine Learning Statistical Approach.
Sports health
Aug 7, 2024
BACKGROUND: This study evaluated 2 different dual-task (DT) conditions during tandem gait (TG) to predict sport-related concussion (SRC) diagnosis.
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