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Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
Breast lesion detection using ultrasound imaging is considered an important step of computer-aided diagnosis systems. Over the past decade, researchers have demonstrated the possibilities to automate the initial lesion detection. However, the lack of...

Matrix and Tensor Completion on a Human Activity Recognition Framework.

IEEE journal of biomedical and health informatics
Sensor-based activity recognition is encountered in innumerable applications of the arena of pervasive healthcare and plays a crucial role in biomedical research. Nonetheless, the frequent situation of unobserved measurements impairs the ability of m...

Deep learning with convolutional neural networks for EEG decoding and visualization.

Human brain mapping
Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end-to-end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end-to-end EEG analysis, but...

A nonparametric Bayesian method of translating machine learning scores to probabilities in clinical decision support.

BMC bioinformatics
BACKGROUND: Probabilistic assessments of clinical care are essential for quality care. Yet, machine learning, which supports this care process has been limited to categorical results. To maximize its usefulness, it is important to find novel approach...

Ghosts in machine learning for cognitive neuroscience: Moving from data to theory.

NeuroImage
The application of machine learning methods to neuroimaging data has fundamentally altered the field of cognitive neuroscience. Future progress in understanding brain function using these methods will require addressing a number of key methodological...

Principles for models of neural information processing.

NeuroImage
The goal of cognitive neuroscience is to understand how mental operations are performed by the brain. Given the complexity of the brain, this is a challenging endeavor that requires the development of formal models. Here, I provide a perspective on m...

Developmental Approach for Behavior Learning Using Primitive Motion Skills.

International journal of neural systems
Imitation learning through self-exploration is essential in developing sensorimotor skills. Most developmental theories emphasize that social interactions, especially understanding of observed actions, could be first achieved through imitation, yet t...
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Active learning reduces annotation time for clinical concept extraction.

International journal of medical informatics
OBJECTIVE: To investigate: (1) the annotation time savings by various active learning query strategies compared to supervised learning and a random sampling baseline, and (2) the benefits of active learning-assisted pre-annotations in accelerating th...
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Measuring Functional Arm Movement after Stroke Using a Single Wrist-Worn Sensor and Machine Learning.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND AND PURPOSE: Trials of restorative therapies after stroke and clinical rehabilitation require relevant and objective efficacy end points; real-world upper extremity (UE) functional use is an attractive candidate. We present a novel, inexpe...

Impact of predicting health-guidance candidates using massive health check-up data: A data-driven analysis.

International journal of medical informatics
INTRODUCTION: Starting in 2008, specific health checkups and health guidance to prevent non-communicable diseases have been provided in Japan, which has the highest proportion of elderly citizens in the world. The attendance rate for health guidance ...