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Making Sense of Spatio-Temporal Preserving Representations for EEG-Based Human Intention Recognition.

IEEE transactions on cybernetics
Brain-computer interface (BCI) is a system empowering humans to communicate with or control the outside world with exclusively brain intentions. Electroencephalography (EEG)-based BCI is one of the promising solutions due to its convenient and portab...

Effectiveness of upper-limb robotic-assisted therapy in the early rehabilitation phase after stroke: A single-blind, randomised, controlled trial.

Annals of physical and rehabilitation medicine
BACKGROUND: Upper-limb robotic-assisted therapy (RAT) is promising for stroke rehabilitation, particularly in the early phase. When RAT is provided as partial substitution of conventional therapy, it is expected to be at least as effective or might b...

Evaluation of a machine learning algorithm for up to 48-hour advance prediction of sepsis using six vital signs.

Computers in biology and medicine
OBJECTIVE: Sepsis remains a costly and prevalent syndrome in hospitals; however, machine learning systems can increase timely sepsis detection using electronic health records. This study validates a gradient boosted ensemble machine learning tool for...

Using Artificial Intelligence to Identify Factors Associated with Autism Spectrum Disorder in Adolescents with Cerebral Palsy.

Neuropediatrics
Autism spectrum disorder (ASD) is common in adolescents with cerebral palsy (CP) and there is a lack of studies applying artificial intelligence to investigate this field and this population in particular. The aim of this study is to develop and test...

Detecting Developmental Delay and Autism Through Machine Learning Models Using Home Videos of Bangladeshi Children: Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Autism spectrum disorder (ASD) is currently diagnosed using qualitative methods that measure between 20-100 behaviors, can span multiple appointments with trained clinicians, and take several hours to complete. In our previous work, we de...

Speech synthesis from neural decoding of spoken sentences.

Nature
Technology that translates neural activity into speech would be transformative for people who are unable to communicate as a result of neurological impairments. Decoding speech from neural activity is challenging because speaking requires very precis...

Diffusion tensor tractography in children with sensory processing disorder: Potentials for devising machine learning classifiers.

NeuroImage. Clinical
The "sensory processing disorder" (SPD) refers to brain's inability to organize sensory input for appropriate use. In this study, we determined the diffusion tensor imaging (DTI) microstructural and connectivity correlates of SPD, and apply machine l...

Deep Learning for Real-time, Automatic, and Scanner-adapted Prostate (Zone) Segmentation of Transrectal Ultrasound, for Example, Magnetic Resonance Imaging-transrectal Ultrasound Fusion Prostate Biopsy.

European urology focus
BACKGROUND: Although recent advances in multiparametric magnetic resonance imaging (MRI) led to an increase in MRI-transrectal ultrasound (TRUS) fusion prostate biopsies, these are time consuming, laborious, and costly. Introduction of deep-learning ...

Development of a robotic walker for individuals with cerebral palsy.

Disability and rehabilitation. Assistive technology
This study describes the first use of a robotic walker in youth and young adults with cerebral palsy (CP) Gross Motor Function Classification (GMFCS) IV. Semi-structured interviews were conducted before and after each robotic walker trial. Interview...