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Showing 1131 to 1140 of 1686 articles

Wearable Sensors for Prodromal Motor Assessment of Parkinson's Disease using Supervised Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Parkinson's disease (PD) is a common neurodegenerative disorder characterized by disabling motor and non-motor symptoms. Idiopathic hyposmia (IH), a reduced olfactory sensitivity, is a preclinical marker for the pathology and affects >95% of PD patie...
Support Vector Machine Algorithms Humans Parkinson Disease Wearable Electronic Devices Olfaction Disorders
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Cardiovascular disease diagnosis using cross-domain transfer learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
While cardiovascular diseases (CVDs) are commonly diagnosed by cardiologists via inspecting electrocardiogram (ECG) waveforms, these decisions can be supported by a data-driven approach, which may automate this process. An automatic diagnostic approa...
Humans Deep Learning Cardiovascular Diseases Electrocardiography Diagnosis, Computer-Assisted
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Detecting Meals In the Wild Using the Inertial Data of a Typical Smartwatch.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Automated and objective monitoring of eating behavior has received the attention of both the research community and the industry over the past few years. In this paper we present a method for automatically detecting meals in free living conditions, u...
Meals Signal Processing, Computer-Assisted Algorithms Feeding Behavior Mobile Applications Humans Neural Networks, Computer
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3D Convolutional Neural Networks for Event-Related Potential detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Deep learning techniques have recently been successful in the classification of brain evoked responses for multiple applications, including brain-machine interface. Single-trial detection in the electroencephalogram (EEG) of brain evoked responses, l...
Neural Networks, Computer Brain Deep Learning Electroencephalography Humans Brain-Computer Interfaces Evoked Potentials
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Deep Learning with Convolutional Neural Network for detecting microsleep states from EEG: A comparison between the oversampling technique and cost-based learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Any occupation which involves critical decision making in real-time requires attention and concentration. When repetitive and expanded working periods are encountered, it can result in microsleeps. Microsleeps are complete lapses in which a subject i...
Deep Learning Electroencephalography Attention Sleep Stages Humans Neural Networks, Computer
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Diagnostic and Prognostic Classification of Brain Disorders Using Residual Learning on Structural MRI Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
In this work, we study the potential of the deep residual neural network (ResNet) architecture to learn abstract neuroanatomical alterations in the structural MRI data by evaluating its diagnostic and prognostic classification performance on two larg...
Brain Diseases Neuroimaging Support Vector Machine Magnetic Resonance Imaging Humans Neural Networks, Computer
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Classification and Assessment of Hand Arthritis Stage using Support Vector Machine.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Arthritis is one of the most common health problems affecting people around the world. The goal of the work presented work is to classify and categorizing hand arthritis stages for patients, who may be developing or have developed hand arthritis, usi...
Arthritis Finger Joint Support Vector Machine Hand Humans Algorithms
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Deep Feature Learning from a Hospital-Scale Chest X-ray Dataset with Application to TB Detection on a Small-Scale Dataset.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
The use of ImageNet pre-trained networks is becoming widespread in the medical imaging community. It enables training on small datasets, commonly available in medical imaging tasks. The recent emergence of a large Chest X-ray dataset opened the possi...
Deep Learning Tuberculosis Humans Neural Networks, Computer Radiography, Thoracic X-Rays
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Right Ventricular Segmentation from MRI Using Deep Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
The assessment of right ventricular (RV) function is essential in the diagnosis of many cardiac diseases. Magnetic resonance imaging (MRI) offers an excellent solution to image right ventricle non-invasively with high contrast and temporal resolution...
Heart Ventricles Humans Neural Networks, Computer Machine Learning Algorithms Image Processing, Computer-Assisted Magnetic Resonance Imaging
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A Multi-channel Deep Learning Approach for Segmentation of the Left Ventricular Endocardium from Cardiac Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Cardiac segmentation is the first most important step in assessing cardiac diseases. However, it still remains challenging owing to the complicated information of myocardium's boundary. In this work, we investigate approaches based on deep learning f...
Neural Networks, Computer Algorithms Humans Heart Ventricles Endocardium Deep Learning Image Processing, Computer-Assisted
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