AIMC Topic: Humans

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Machine learning in resting-state fMRI analysis.

Magnetic resonance imaging Jun 5, 2019
Machine learning techniques have gained prominence for the analysis of resting-state functional Magnetic Resonance Imaging (rs-fMRI) data. Here, we present an overview of various unsupervised and supervised machine learning applications to rs-fMRI. W...
Humans Brain Mapping Image Interpretation, Computer-Assisted Magnetic Resonance Imaging Brain Diseases Rest Brain Female Machine Learning Male Algorithms
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[Application of deep learning for the occupational health of VDT workers].

Sangyo eiseigaku zasshi = Journal of occupational health Jun 5, 2019
Female Young Adult Adult Humans Computer Terminals Deep Learning Occupational Health Male
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SANTIS: Sampling-Augmented Neural neTwork with Incoherent Structure for MR image reconstruction.

Magnetic resonance in medicine Jun 5, 2019
PURPOSE: To develop and evaluate a novel deep learning-based reconstruction framework called SANTIS (Sampling-Augmented Neural neTwork with Incoherent Structure) for efficient MR image reconstruction with improved robustness against sampling pattern ...
Humans Neural Networks, Computer Image Interpretation, Computer-Assisted Knee Gadolinium DTPA Magnetic Resonance Imaging Liver Contrast Media
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Machine Learning Groups Patients by Early Functional Improvement Likelihood Based on Wearable Sensor Instrumented Preoperative Timed-Up-and-Go Tests.

The Journal of arthroplasty Jun 5, 2019
BACKGROUND: Wearable sensors permit efficient data collection and unobtrusive systems can be used for instrumenting knee patients for objective assessment. Machine learning can be leveraged to parse the abundant information these systems provide and ...
Osteoarthritis, Knee Aged, 80 and over Algorithms Humans Time and Motion Studies Wearable Electronic Devices Male Machine Learning Female Knee Joint Postural Balance Middle Aged Aged Arthroplasty, Replacement, Knee
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Quantifying performance of machine learning methods for neuroimaging data.

NeuroImage Jun 5, 2019
Machine learning is increasingly being applied to neuroimaging data. However, most machine learning algorithms have not been designed to accommodate neuroimaging data, which typically has many more data points than subjects, in addition to multicolli...
Humans Reproducibility of Results Machine Learning Models, Theoretical Brain Neuroimaging
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Machine Learning for the Interventional Radiologist.

AJR. American journal of roentgenology Jun 5, 2019
The purpose of this article is to describe key potential areas of application of machine learning in interventional radiology. Machine learning, although in the early stages of development within the field of interventional radiology, has great pot...
Humans Machine Learning Radiology, Interventional
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Concepts in U.S. Food and Drug Administration Regulation of Artificial Intelligence for Medical Imaging.

AJR. American journal of roentgenology Jun 5, 2019
Although extensive attention has been focused on the enormous potential of artificial intelligence (AI) technology, a major question remains: how should this fundamentally new technology be regulated? The purpose of this article is to provide an ove...
United States Food and Drug Administration United States Diagnostic Imaging Humans Patient Safety Algorithms Artificial Intelligence Clinical Competence
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A review on brain tumor diagnosis from MRI images: Practical implications, key achievements, and lessons learned.

Magnetic resonance imaging Jun 5, 2019
The successful early diagnosis of brain tumors plays a major role in improving the treatment outcomes and thus improving patient survival. Manually evaluating the numerous magnetic resonance imaging (MRI) images produced routinely in the clinic is a ...
Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Algorithms Magnetic Resonance Imaging Glioma Humans Brain Machine Learning Brain Neoplasms
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Modeling longitudinal imaging biomarkers with parametric Bayesian multi-task learning.

Human brain mapping Jun 5, 2019
Longitudinal imaging biomarkers are invaluable for understanding the course of neurodegeneration, promising the ability to track disease progression and to detect disease earlier than cross-sectional biomarkers. To properly realize their potential, b...
Cerebral Cortex Magnetic Resonance Imaging Bayes Theorem Datasets as Topic Neuroimaging Alzheimer Disease Computer Simulation Models, Theoretical Longitudinal Studies Humans Machine Learning Biomarkers
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Artificial Intelligence in Musculoskeletal Imaging: Current Status and Future Directions.

AJR. American journal of roentgenology Jun 5, 2019
The objective of this article is to show how artificial intelligence (AI) has impacted different components of the imaging value chain thus far as well as to describe its potential future uses. The use of AI has the potential to greatly enhance eve...
Artificial Intelligence Humans Forecasting Musculoskeletal Diseases
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