AIMC Topic: Humans

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Changes to information in working memory depend on distinct removal operations.

Nature communications
Holding information in working memory is essential for cognition, but removing unwanted thoughts is equally important. Here we use multivariate pattern analyses of brain activity to demonstrate the successful manipulation and removal of information f...

Predicting 30-days mortality for MIMIC-III patients with sepsis-3: a machine learning approach using XGboost.

Journal of translational medicine
BACKGROUND: Sepsis is a significant cause of mortality in-hospital, especially in ICU patients. Early prediction of sepsis is essential, as prompt and appropriate treatment can improve survival outcomes. Machine learning methods are flexible predicti...

Deep learning to diagnose cardiac amyloidosis from cardiovascular magnetic resonance.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Cardiovascular magnetic resonance (CMR) is part of the diagnostic work-up for cardiac amyloidosis (CA). Deep learning (DL) is an application of artificial intelligence that may allow to automatically analyze CMR findings and establish the...

A biomimetic soft robotic pinna for emulating dynamic reception behavior of horseshoe bats.

Bioinspiration & biomimetics
Encoding of sensory information is fundamental to closing the performance gap between man-made and biological sensing. It has been hypothesized that the coupling of sensing and actuation, a phenomenon observed in bats among other species, is critical...

The realization of robotic neurorehabilitation in clinical: use of computational intelligence and future prospects analysis.

Expert review of medical devices
: Although there is a need for rehabilitation treatment with the increase in the aging population, the shortage of skilled physicians frustrates this necessity. Robotic technology has been advocated as one of the most viable methods with the potentia...

A Multifrequency Brain Network-Based Deep Learning Framework for Motor Imagery Decoding.

Neural plasticity
Motor imagery (MI) is an important part of brain-computer interface (BCI) research, which could decode the subject's intention and help remodel the neural system of stroke patients. Therefore, accurate decoding of electroencephalography- (EEG-) based...

Accurate spatiotemporal mapping of drug overdose deaths by machine learning of drug-related web-searches.

PloS one
Persons who inject drugs (PWID) are at increased risk for overdose death (ODD), infections with HIV, hepatitis B (HBV) and hepatitis C virus (HCV), and noninfectious health conditions. Spatiotemporal identification of PWID communities is essential fo...

Data classification based on fractional order gradient descent with momentum for RBF neural network.

Network (Bristol, England)
The weight-updating methods have played an important role in improving the performance of neural networks. To ameliorate the oscillating phenomenon in training radial basis function (RBF) neural network, a fractional order gradient descent with momen...

Social robots and therapeutic adherence: A new challenge in pediatric asthma?

Paediatric respiratory reviews
Social Robots are used in different contexts and, in healthcare, they are better known as Socially Assistive Robots. In the context of asthma, the use of Socially Assistive Robots has the potential to increase motivation and engagement to treatment. ...