AIMC Topic: Machine Learning

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A hybrid machine learning/deep learning COVID-19 severity predictive model from CT images and clinical data.

Scientific reports
COVID-19 clinical presentation and prognosis are highly variable, ranging from asymptomatic and paucisymptomatic cases to acute respiratory distress syndrome and multi-organ involvement. We developed a hybrid machine learning/deep learning model to c...

Coal Mine Safety Evaluation Based on Machine Learning: A BP Neural Network Model.

Computational intelligence and neuroscience
As the core of artificial intelligence, machine learning has strong application advantages in multi-criteria intelligent evaluation and decision-making. The level of sustainable development is of great significance to the safety evaluation of coal mi...

PhosVarDeep: deep-learning based prediction of phospho-variants using sequence information.

PeerJ
Human DNA sequencing has revealed numerous single nucleotide variants associated with complex diseases. Researchers have shown that these variants have potential effects on protein function, one of which is to disrupt protein phosphorylation. Based o...

Gauging the Impact of Artificial Intelligence and Mathematical Modeling in Response to the COVID-19 Pandemic: A Systematic Review.

BioMed research international
While the world continues to grapple with the devastating effects of the SARS-nCoV-2 virus, different scientific groups, including researchers from different parts of the world, are trying to collaborate to discover solutions to prevent the spread of...

Generative machine learning for de novo drug discovery: A systematic review.

Computers in biology and medicine
Recent research on artificial intelligence indicates that machine learning algorithms can auto-generate novel drug-like molecules. Generative models have revolutionized de novo drug discovery, rendering the explorative process more efficient. Several...

Artificial intelligence approaches to the biochemistry of oxidative stress: Current state of the art.

Chemico-biological interactions
Artificial intelligence (AI) and machine learning models are today frequently used for classification and prediction of various biochemical processes and phenomena. In recent years, numerous research efforts have been focused on developing such model...

An Ensemble Learning Model for COVID-19 Detection from Blood Test Samples.

Sensors (Basel, Switzerland)
Current research endeavors in the application of artificial intelligence (AI) methods in the diagnosis of the COVID-19 disease has proven indispensable with very promising results. Despite these promising results, there are still limitations in real-...

Incremental Ant-Miner Classifier for Online Big Data Analytics.

Sensors (Basel, Switzerland)
Internet of Things (IoT) environments produce large amounts of data that are challenging to analyze. The most challenging aspect is reducing the quantity of consumed resources and time required to retrain a machine learning model as new data records ...

Efficient Violence Detection in Surveillance.

Sensors (Basel, Switzerland)
Intelligent video surveillance systems are rapidly being introduced to public places. The adoption of computer vision and machine learning techniques enables various applications for collected video features; one of the major is safety monitoring. Th...

A machine learning approach to identify stochastic resonance in human perceptual thresholds.

Journal of neuroscience methods
BACKGROUND: Stochastic resonance (SR) is achieved when a faint signal is improved with the addition of the appropriate amount of white noise. Perceptual thresholds are expected to follow a characteristic performance improvement curve as a function of...