AIMC Topic: Healthy Volunteers

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Transferring a deep learning model from healthy subjects to stroke patients in a motor imagery brain-computer interface.

Journal of neural engineering Jan 17, 2024
Motor imagery (MI) brain-computer interfaces (BCIs) based on electroencephalogram (EEG) have been developed primarily for stroke rehabilitation, however, due to limited stroke data, current deep learning methods for cross-subject classification rely ...
Algorithms Deep Learning Electroencephalography Humans Stroke Brain-Computer Interfaces Healthy Volunteers Imagination Imagery, Psychotherapy
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Diagnostic deep learning algorithms that use resting EEG to distinguish major depressive disorder, bipolar disorder, and schizophrenia from each other and from healthy volunteers.

Journal of affective disorders Nov 12, 2023
BACKGROUND: Mood disorders and schizophrenia affect millions worldwide. Currently, diagnosis is primarily determined by reported symptomatology. As symptoms may overlap, misdiagnosis is common, potentially leading to ineffective or destabilizing trea...
Healthy Volunteers Humans Electroencephalography Bipolar Disorder Schizophrenia Depressive Disorder, Major Deep Learning
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Reconstruction of shoulder MRI using deep learning and compressed sensing: a validation study on healthy volunteers.

European radiology experimental Oct 26, 2023
BACKGROUND: To investigate the potential of combining compressed sensing (CS) and deep learning (DL) for accelerated two-dimensional (2D) and three-dimensional (3D) magnetic resonance imaging (MRI) of the shoulder.
Humans Deep Learning Imaging, Three-Dimensional Shoulder Magnetic Resonance Imaging Healthy Volunteers
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Predicting 'Brainage' in late childhood to adolescence (6-17yrs) using structural MRI, morphometric similarity, and machine learning.

Scientific reports Sep 20, 2023
Brain development is regularly studied using structural MRI. Recently, studies have used a combination of statistical learning and large-scale imaging databases of healthy children to predict an individual's age from structural MRI. This data-driven,...
Child Magnetic Resonance Imaging Databases, Factual Adolescent Benchmarking Healthy Volunteers Humans Machine Learning
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Artificially-generated consolidations and balanced augmentation increase performance of U-net for lung parenchyma segmentation on MR images.

PloS one May 9, 2023
PURPOSE: To improve automated lung segmentation on 2D lung MR images using balanced augmentation and artificially-generated consolidations for training of a convolutional neural network (CNN).
Humans Healthy Volunteers Neural Networks, Computer Thorax Lung Semantic Web
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A deep learning-based reconstruction approach for accelerated magnetic resonance image of the knee with compressed sense: evaluation in healthy volunteers.

The British journal of radiology Apr 22, 2023
OBJECTIVES: To evaluate the feasibility of combining compressed sense (CS) with a newly developed deep learning-based algorithm (CS-AI) using convolutional neural networks to accelerate 2D MRI of the knee.
Magnetic Resonance Imaging Knee Joint Healthy Volunteers Imaging, Three-Dimensional Image Processing, Computer-Assisted Prospective Studies Deep Learning Humans
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A Novel Tactile Function Assessment Using a Miniature Tactile Stimulator.

Sensors (Basel, Switzerland) Feb 7, 2023
Several methods for the measurement of tactile acuity have been devised previously, but unexpected nonspatial cues and intensive manual skill requirements compromise measurement accuracy. Therefore, we must urgently develop an automated, accurate, an...
Robotics Rotation Cues Healthy Volunteers Humans
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A machine-learning algorithm for predicting brain age using Rey-Osterrieth complex figure tests of healthy participants.

Applied neuropsychology. Adult Jan 12, 2023
OBJECTIVE: Neuropsychologists widely use the Rey-Osterrieth complex figure test (RCFT) as part of neuropsychological test batteries to evaluate cognitive function and assess constructional ability, with age being the most significant factor. Our stud...
Aged Aged, 80 and over Aging Middle Aged Male Brain Female Humans Machine Learning Neuropsychological Tests Supervised Machine Learning Healthy Volunteers
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Automated Measurement of Ocular Movements Using Deep Learning-Based Image Analysis.

Current eye research Jul 27, 2022
PURPOSE: Clinical assessment of ocular movements is essential for the diagnosis and management of ocular motility disorders. This study aimed to propose a deep learning-based image analysis to automatically measure ocular movements based on photograp...
Eye Movements Oculomotor Muscles Humans Healthy Volunteers Ocular Motility Disorders Deep Learning
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Commercially Available Deep-learning-reconstruction of MR Imaging of the Knee at 1.5T Has Higher Image Quality Than Conventionally-reconstructed Imaging at 3T: A Normal Volunteer Study.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Jul 9, 2022
PURPOSE: This study aimed to evaluate whether the image quality of 1.5T magnetic resonance imaging (MRI) of the knee is equal to or higher than that of 3T MRI by applying deep learning reconstruction (DLR).
Cartilage, Articular Knee Joint Deep Learning Humans Healthy Volunteers Magnetic Resonance Imaging
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