AIMC Topic: Humans

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Unsupervised Learning in RSS-Based DFLT Using an EM Algorithm.

Sensors (Basel, Switzerland)
Received signal strength (RSS) changes of static wireless nodes can be used for device-free localization and tracking (DFLT). Most RSS-based DFLT systems require access to calibration data, either RSS measurements from a time period when the area was...

Lead Reconstruction Using Artificial Neural Networks for Ambulatory ECG Acquisition.

Sensors (Basel, Switzerland)
One of the most powerful techniques to diagnose cardiovascular diseases is to analyze the electrocardiogram (ECG). To increase diagnostic sensitivity, the ECG might need to be acquired using an ambulatory system, as symptoms may occur during a patien...

Cancer-associated fibroblasts are associated with poor prognosis in solid type of lung adenocarcinoma in a machine learning analysis.

Scientific reports
Cancer-associated fibroblasts (CAFs) participate in critical processes in the tumor microenvironment, such as extracellular matrix remodeling, reciprocal signaling interactions with cancer cells and crosstalk with infiltrating inflammatory cells. How...

Predicting pediatric anxiety from the temporal pole using neural responses to emotional faces.

Scientific reports
A prominent cognitive aspect of anxiety is dysregulation of emotional interpretation of facial expressions, associated with neural activity from the amygdala and prefrontal cortex. We report machine learning analysis of fMRI results supporting a key ...

Performance of Fully Automated Antimicrobial Disk Diffusion Susceptibility Testing Using Copan WASP Colibri Coupled to the Radian In-Line Carousel and Expert System.

Journal of clinical microbiology
The purpose of the present study was to assess the agreement at the categorical level between the Vitek 2 system and the Colibri coupled to the Radian under real routine laboratory conditions. The 675 nonduplicate clinical strains included in this st...

The Growing Role for Semantic Segmentation in Urology.

European urology focus
As the quantity and quality of cross-sectional imaging data increase, it is important to be able to make efficient use of the information. Semantic segmentation is an emerging technology that promises to improve the speed, reproducibility, and accura...

Multilevel Strip Pooling-Based Convolutional Neural Network for the Classification of Carotid Plaque Echogenicity.

Computational and mathematical methods in medicine
Carotid plaque echogenicity in ultrasound images has been found to be closely correlated with the risk of stroke in atherosclerotic patients. The automatic and accurate classification of carotid plaque echogenicity is of great significance for clinic...

Skeleton-Based Action Recognition Based on Distance Vector and Multihigh View Adaptive Networks.

Computational intelligence and neuroscience
Skeleton-based human action recognition has attracted much attention in the field of computer vision. Most of the previous studies are based on fixed skeleton graphs so that only the local physical dependencies among joints can be captured, resulting...

Dynamic graph convolutional networks with attention mechanism for rumor detection on social media.

PloS one
Social media has become an ideal platform for the propagation of rumors, fake news, and misinformation. Rumors on social media not only mislead online users but also affect the real world immensely. Thus, detecting the rumors and preventing their spr...

Sexing white 2D footprints using convolutional neural networks.

PloS one
Footprints are left, or obtained, in a variety of scenarios from crime scenes to anthropological investigations. Determining the sex of a footprint can be useful in screening such impressions and attempts have been made to do so using single or multi...