AIMC Topic: Machine Learning

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Use of Machine Learning to Model Volume Load Effects on Changes in Jump Performance.

International journal of sports physiology and performance
PURPOSE: To use an artificial neural network (ANN) to model the effect of 15 weeks of resistance training on changes in countermovement jump (CMJ) performance in male track-and-field athletes.

Measuring and improving adaptive capacity in resilient systems by means of an integrated DEA-Machine learning approach.

Applied ergonomics
Resilient systems strive to enhance the safety of complex systems through building and developing adaptive technological and organizational capacities. This study aims at analyzing and improving the level of adaptive capacity in a petrochemical plant...

PARS, a system combining semantic technologies with multiple criteria decision aiding for supporting antibiotic prescriptions.

Journal of biomedical informatics
OBJECTIVE: Motivated by the well documented worldwide spread of adverse drug events, as well as the increased danger of antibiotic resistance (caused mainly by inappropriate prescribing and overuse), we propose a novel recommendation system for antib...

Machine learning-guided channelrhodopsin engineering enables minimally invasive optogenetics.

Nature methods
We engineered light-gated channelrhodopsins (ChRs) whose current strength and light sensitivity enable minimally invasive neuronal circuit interrogation. Current ChR tools applied to the mammalian brain require intracranial surgery for transgene deli...

D-GPM: A Deep Learning Method for Gene Promoter Methylation Inference.

Genes
Whole-genome bisulfite sequencing generates a comprehensive profiling of the gene methylation levels, but is limited by a high cost. Recent studies have partitioned the genes into landmark genes and target genes and suggested that the landmark gene e...

A comparative study of machine learning classifiers for risk prediction of asthma disease.

Photodiagnosis and photodynamic therapy
Asthma is a chronic disease characterized by wheezing, chest tightening and difficulty in breathing due to inflammation of lung airways. Early risk prediction of asthma is crucial for proper and effective management. This study presents the use of ma...

Applications of Artificial Intelligence in Cardiology. The Future is Already Here.

Revista espanola de cardiologia (English ed.)
There is currently no other hot topic like the ability of current technology to develop capabilities similar to those of human beings, even in medicine. This ability to simulate the processes of human intelligence with computer systems is known as ar...

Deep neural networks and kernel regression achieve comparable accuracies for functional connectivity prediction of behavior and demographics.

NeuroImage
There is significant interest in the development and application of deep neural networks (DNNs) to neuroimaging data. A growing literature suggests that DNNs outperform their classical counterparts in a variety of neuroimaging applications, yet there...

A machine learning approach for the identification of population-informative markers from high-throughput genotyping data: application to several pig breeds.

Animal : an international journal of animal bioscience
Single nucleotide polymorphisms (SNPs) able to describe population differences can be used for important applications in livestock, including breed assignment of individual animals, authentication of mono-breed products and parentage verification amo...