AIMC Topic: Algorithms

Clear Filters Showing 12061 to 12070 of 28713 articles

Artificial Intelligence for Colonoscopy: Past, Present, and Future.

IEEE journal of biomedical and health informatics
During the past decades, many automated image analysis methods have been developed for colonoscopy. Real-time implementation of the most promising methods during colonoscopy has been tested in clinical trials, including several recent multi-center st...

Multi-Scale Convolutional Neural Network Ensemble for Multi-Class Arrhythmia Classification.

IEEE journal of biomedical and health informatics
The automated analysis of electrocardiogram (ECG) signals plays a crucial role in the early diagnosis and management of cardiac arrhythmias. The diverse etiology of arrhythmia and the subtle variations in the pathological ECG characteristics pose cha...

Deep Learning-Based Data Augmentation and Model Fusion for Automatic Arrhythmia Identification and Classification Algorithms.

Computational intelligence and neuroscience
Automated ECG-based arrhythmia detection is critical for early cardiac disease prevention and diagnosis. Recently, deep learning algorithms have been widely applied for arrhythmia detection with great success. However, the lack of labeled ECG data an...

Prioritized and predictive intelligence of things enabled waste management model in smart and sustainable environment.

PloS one
Collaborative modelling of the Internet of Things (IoT) with Artificial Intelligence (AI) has merged into the Intelligence of Things concept. This recent trend enables sensors to track required parameters and store accumulated data in cloud storage, ...

A privacy preservation framework for feedforward-designed convolutional neural networks.

Neural networks : the official journal of the International Neural Network Society
A feedforward-designed convolutional neural network (FF-CNN) is an interpretable neural network with low training complexity. Unlike a neural network trained using backpropagation (BP) algorithms and optimizers (e.g., stochastic gradient descent (SGD...

Brain-inspired chaotic backpropagation for MLP.

Neural networks : the official journal of the International Neural Network Society
Backpropagation (BP) algorithm is one of the most basic learning algorithms in deep learning. Although BP has been widely used, it still suffers from the problem of easily falling into the local minima due to its gradient dynamics. Inspired by the fa...

Assessment of patient based real-time quality control on comparative assays for common clinical analytes.

Journal of clinical laboratory analysis
BACKGROUND: It is critical for laboratories to conduct multianalyzer comparisons as a part of daily routine work to strengthen the quality management of test systems. Here, we explored the application of patient-based real-time quality controls (PBRT...

Digital computing through randomness and order in neural networks.

Proceedings of the National Academy of Sciences of the United States of America
We propose that coding and decoding in the brain are achieved through digital computation using three principles: relative ordinal coding of inputs, random connections between neurons, and belief voting. Due to randomization and despite the coarsenes...

A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method.

Sensors (Basel, Switzerland)
Due to the rapid growth in IT technology, digital data have increased availability, creating novel security threats that need immediate attention. An intrusion detection system (IDS) is the most promising solution for preventing malicious intrusions ...

A Conditional GAN for Generating Time Series Data for Stress Detection in Wearable Physiological Sensor Data.

Sensors (Basel, Switzerland)
Human-centered applications using wearable sensors in combination with machine learning have received a great deal of attention in the last couple of years. At the same time, wearable sensors have also evolved and are now able to accurately measure p...