AI Medical Compendium Topic:
Pattern Recognition, Automated

Clear Filters Showing 681 to 690 of 1638 articles

Automatic Lacunae Localization in Placental Ultrasound Images via Layer Aggregation.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Accurate localization of structural abnormalities is a precursor for image-based prenatal assessment of adverse conditions. For clinical screening and diagnosis of abnormally invasive placenta (AIP), a life-threatening obstetric condition, qualitativ...

ECG signal classification for the detection of cardiac arrhythmias using a convolutional recurrent neural network.

Physiological measurement
OBJECTIVE: The electrocardiogram (ECG) provides an effective, non-invasive approach for clinical diagnosis in patients with cardiac diseases such as atrial fibrillation (AF). AF is the most common cardiac rhythm disturbance and affects ~2% of the gen...

Application of identity vectors for EEG classification.

Journal of neuroscience methods
BACKGROUND: Finding an optimal EEG subject verification algorithm is a long standing goal within the EEG community. For every advancement made, another feature set, classifier, or dataset is often introduced; tracking improvements in classification w...

A Continuously Updated, Computationally Efficient Stress Recognition Framework Using Electroencephalogram (EEG) by Applying Online Multitask Learning Algorithms (OMTL).

IEEE journal of biomedical and health informatics
Recognizing the factors that cause stress is a crucial step toward early detection of stressors. In this regard, several studies make an effort to recognize individuals' stress using an Electroencephalogram (EEG). However, current EEG-based stress re...

Parallel use of a convolutional neural network and bagged tree ensemble for the classification of Holter ECG.

Physiological measurement
UNLABELLED: The automated detection of arrhythmia in a Holter ECG signal is a challenging task due to its complex clinical content and data quantity. It is also challenging due to the fact that Holter ECG is usually affected by noise. Such noise may ...

Real-time, simultaneous myoelectric control using a convolutional neural network.

PloS one
The evolution of deep learning techniques has been transformative as they have allowed complex mappings to be trained between control inputs and outputs without the need for feature engineering. In this work, a myoelectric control system based on con...

Critical features for face recognition.

Cognition
Face recognition is a computationally challenging task that humans perform effortlessly. Nonetheless, this remarkable ability is better for familiar faces than unfamiliar faces. To account for humans' superior ability to recognize familiar faces, cur...

Smartwatch User Interface Implementation Using CNN-Based Gesture Pattern Recognition.

Sensors (Basel, Switzerland)
In recent years, with an increase in the use of smartwatches among wearable devices, various applications for the device have been developed. However, the realization of a user interface is limited by the size and volume of the smartwatch. This study...

Control within a virtual environment is correlated to functional outcomes when using a physical prosthesis.

Journal of neuroengineering and rehabilitation
BACKGROUND: Advances such as targeted muscle reinnervation and pattern recognition control may provide improved control of upper limb myoelectric prostheses, but evaluating user function remains challenging. Virtual environments are cost-effective an...