An ambulatory elder with SCI, AIS C, balance deficits, and right ankle-foot-orthosis participated. RobUST-intervention comprised six 90 min-sessions of postural tasks with pelvic assistance and trunk perturbations. We collected three baselines and tw...
BACKGROUND: Currently, the risk stratification of critically ill patient with chest pain is a challenge. We aimed to use machine learning approach to predict the critical care outcomes in patients with chest pain, and simultaneously compare its perfo...
Due to rapid developments in machine learning, and in particular neural networks, a number of new methods for time-to-event predictions have been developed in the last few years. As neural networks are parametric models, it is more straightforward to...
OBJECTIVE: No accurate predictive models were identified for hormonal prognosis in non-functioning pituitary adenoma (NFPA). This study aimed to develop machine learning (ML) models to facilitate the prognostic assessment of pituitary hormonal outcom...
In order to discuss the clinical characteristics of patients with scapular fracture, deep learning model was adopted in ultrasound images of patients to locate the anesthesia point of patients during scapular fracture surgery treated with the regiona...
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
Brain-Computer interfaces (BCIs) enhance the capability of human brain activities to interact with the environment. Recent advancements in technology and machine learning algorithms have increased interest in electroencephalographic (EEG)-based BCI a...
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
At present, the application of Electroencephalogram (EEG) signal classification to human intention-behavior prediction has become a hot topic in the brain computer interface (BCI) research field. In recent studies, the introduction of convolutional n...
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
The rapid development of high-throughput sequencing technology provides unique opportunities for studying of transcription factor binding sites, but also brings new computational challenges. Recently, a series of discriminative motif discovery (DMD) ...
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
Electroencephalogram (EEG) is a non-invasive collection method for brain signals. It has broad prospects in brain-computer interface (BCI) applications. Recent advances have shown the effectiveness of the widely used convolutional neural network (CNN...
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
Affective computing is one of the key technologies to achieve advanced brain-machine interfacing. It is increasingly concerning research orientation in the field of artificial intelligence. Emotion recognition is closely related to affective computin...
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