AI Medical Compendium Topic

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Artificial intelligence in perioperative medicine: a narrative review.

Korean journal of anesthesiology
Recent advancements in artificial intelligence (AI) techniques have enabled the development of accurate prediction models using clinical big data. AI models for perioperative risk stratification, intraoperative event prediction, biosignal analyses, a...

A Three-Stage Dynamic Assessment Framework for Industrial Control System Security Based on a Method of W-HMM.

Sensors (Basel, Switzerland)
Industrial control systems (ICS) are applied in many fields. Due to the development of cloud computing, artificial intelligence, and big data analysis inducing more cyberattacks, ICS always suffers from the risks. If the risks occur during system ope...

A Rumor Detection Method from Social Network Based on Deep Learning in Big Data Environment.

Computational intelligence and neuroscience
Aiming at the lack of feature extraction ability of rumor detection methods based on the deep learning model, this study proposes a rumor detection method based on deep learning in social network big data environment. Firstly, the scheme of combining...

Application of a Hybrid Model of Big Data and BP Network on Fault Diagnosis Strategy for Microgrid.

Computational intelligence and neuroscience
Aiming at the characteristics of timely transmission, rapid update, and large magnitude of microgrid data, based on the large data samples generated by microgrid operation, a fault diagnosis and analysis method of microgrid systems supported by big d...

Industry 4.0 Technologies Applied to the Rail Transportation Industry: A Systematic Review.

Sensors (Basel, Switzerland)
BACKGROUND: Industry 4.0 technologies have been widely used in the railway industry, focusing mainly on maintenance and control tasks necessary in the railway infrastructure. Given the great potential that these technologies offer, the scientific com...

A Novel Reformed Reduced Kernel Extreme Learning Machine with RELIEF-F for Classification.

Computational intelligence and neuroscience
With the exponential growth of the Internet population, scientists and researchers face the large-scale data for processing. However, the traditional algorithms, due to their complex computation, are not suitable for the large-scale data, although th...

Deep convolutional neural network-based signal quality assessment for photoplethysmogram.

Computers in biology and medicine
Quality assessment of bio-signals is important to prevent clinical misdiagnosis. With the introduction of mobile and wearable health care, it is becoming increasingly important to distinguish available signals from noise. The goal of this study was t...

An Empirical Evaluation of Network Representation Learning Methods.

Big data
Network representation learning methods map network nodes to vectors in an embedding space that can preserve specific properties and enable traditional downstream prediction tasks. The quality of the representations learned is then generally showcase...

Are batch effects still relevant in the age of big data?

Trends in biotechnology
Batch effects (BEs) are technical biases that may confound analysis of high-throughput biotechnological data. BEs are complex and effective mitigation is highly context-dependent. In particular, the advent of high-resolution technologies such as sing...

New Progress in Artificial Intelligence Algorithm Research Based on Big Data Processing of IOT Systems on Intelligent Production Lines.

Computational intelligence and neuroscience
Intelligent production line is the abbreviation of intelligent production line. Intelligent production line refers to a form of production organization that uses intelligent manufacturing technology to realize the production process of products. The ...