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A computer vision approach for classifying isometric grip force exertion levels.
Ergonomics
Apr 10, 2020
Exposure to high and/or repetitive force exertions can lead to musculoskeletal injuries. However, measuring worker force exertion levels is challenging, and existing techniques can be intrusive, interfere with human-machine interface, and/or limited ...
Tensor-Based Emotional Category Classification via Visual Attention-Based Heterogeneous CNN Feature Fusion.
Sensors (Basel, Switzerland)
Apr 10, 2020
The paper proposes a method of visual attention-based emotion classification through eye gaze analysis. Concretely, tensor-based emotional category classification via visual attention-based heterogeneous convolutional neural network (CNN) feature fus...
Automatic diagnosis of the 12-lead ECG using a deep neural network.
Nature communications
Apr 9, 2020
The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. Deep Neural Networks (DNNs) are models composed of stacked transformations that learn tasks by examples. This technology has re...
Quantitative Assessment of Motor Function for Patients with a Stroke by an End-Effector Upper Limb Rehabilitation Robot.
BioMed research international
Apr 8, 2020
With the popularization of rehabilitation robots, it is necessary to develop quantitative motor function assessment methods for patients with a stroke. To make the assessment equipment easier to use in clinics and combine the assessment methods with ...
A Machine Learning Approach for High-Dimensional Time-to-Event Prediction With Application to Immunogenicity of Biotherapies in the ABIRISK Cohort.
Frontiers in immunology
Apr 7, 2020
Predicting immunogenicity for biotherapies using patient and drug-related factors represents nowadays a challenging issue. With the growing ability to collect massive amount of data, machine learning algorithms can provide efficient predictive tools....
Multivariate patterns of EEG microstate parameters and their role in the discrimination of patients with schizophrenia from healthy controls.
Psychiatry research
Apr 6, 2020
Quasi-stable electrical fields in the EEG, called microstates carry information on the dynamics of large scale brain networks. Using machine learning techniques, we explored whether abnormalities in microstates can be used to classify patients with s...
Achieving affective human-virtual agent communication by enabling virtual agents to imitate positive expressions.
Scientific reports
Apr 6, 2020
Affective communication, communicating with emotion, during face-to-face communication is critical for social interaction. Advances in artificial intelligence have made it essential to develop affective human-virtual agent communication. A person's b...
Deep learning-based cancer survival prognosis from RNA-seq data: approaches and evaluations.
BMC medical genomics
Apr 3, 2020
BACKGROUND: Recent advances in kernel-based Deep Learning models have introduced a new era in medical research. Originally designed for pattern recognition and image processing, Deep Learning models are now applied to survival prognosis of cancer pat...
Automatic detection of cortical arousals in sleep and their contribution to daytime sleepiness.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Apr 2, 2020
OBJECTIVE: Significant interscorer variability is found in manual scoring of arousals in polysomnographic recordings (PSGs). We propose a fully automatic method, the Multimodal Arousal Detector (MAD), for detecting arousals.
Comparison of Xpert MTB/RIF (G4) and Xpert Ultra, including trace readouts, for the diagnosis of pulmonary tuberculosis in a TB and HIV endemic setting.
International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
Apr 2, 2020
BACKGROUND: There are limited data about Xpert-Ultra performance in different settings, in HIV-infected persons, in those with a history of previous TB, and with trace readouts.
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