AI Medical Compendium Topic:
Pattern Recognition, Automated

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Predicting Athlete Ground Reaction Forces and Moments From Spatio-Temporal Driven CNN Models.

IEEE transactions on bio-medical engineering
The accurate prediction of three-dimensional (3-D) ground reaction forces and moments (GRF/Ms) outside the laboratory setting would represent a watershed for on-field biomechanical analysis. To extricate the biomechanist's reliance on ground embedded...

Unsupervised Domain Adaptation for Facial Expression Recognition Using Generative Adversarial Networks.

Computational intelligence and neuroscience
In the facial expression recognition task, a good-performing convolutional neural network (CNN) model trained on one dataset (source dataset) usually performs poorly on another dataset (target dataset). This is because the feature distribution of the...

Scaling up molecular pattern recognition with DNA-based winner-take-all neural networks.

Nature
From bacteria following simple chemical gradients to the brain distinguishing complex odour information, the ability to recognize molecular patterns is essential for biological organisms. This type of information-processing function has been implemen...

A Visual Cortex-Inspired Imaging-Sensor Architecture and Its Application in Real-Time Processing.

Sensors (Basel, Switzerland)
For robots equipped with an advanced computer vision-based system, object recognition has stringent real-time requirements. When the environment becomes complicated and keeps changing, existing works (e.g., template-matching strategy and machine-lear...

Reproducibility of importance extraction methods in neural network based fMRI classification.

NeuroImage
Recent advances in machine learning allow faster training, improved performance and increased interpretability of classification techniques. Consequently, their application in neuroscience is rapidly increasing. While classification approaches have p...

The effect of structure on image classification using signatures.

Biological cybernetics
Humans recognize transformed images from a very small number of samples. Inspired by this idea, we evaluate a classification method that requires only one sample per class, while providing invariance to image transformations generated by a compact gr...

Epigenetic machine learning: utilizing DNA methylation patterns to predict spastic cerebral palsy.

BMC bioinformatics
BACKGROUND: Spastic cerebral palsy (CP) is a leading cause of physical disability. Most people with spastic CP are born with it, but early diagnosis is challenging, and no current biomarker platform readily identifies affected individuals. The aim of...

Survey and experimental study on metric learning methods.

Neural networks : the official journal of the International Neural Network Society
Distance metric learning has been a hot research spot recently due to its high effectiveness and efficiency in improving the performance of distance related methods, such as k nearest neighbors (kNN). Metric learning aims to learn a data-dependent me...

A distance measure between intuitionistic fuzzy sets and its application in medical diagnosis.

Artificial intelligence in medicine
The intuitionistic fuzzy set, as a generation of fuzzy set, can express and process uncertainty much better. Distance measures between intuitionistic fuzzy sets are used to indicate the difference degree between the information carried by intuitionis...

Impact of Sliding Window Length in Indoor Human Motion Modes and Pose Pattern Recognition Based on Smartphone Sensors.

Sensors (Basel, Switzerland)
Human activity recognition (HAR) is essential for understanding people’s habits and behaviors, providing an important data source for precise marketing and research in psychology and sociology. Different approaches have been proposed and applie...