AIMC Topic: Markov Chains

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Asynchronous dissipative filtering for nonhomogeneous Markov switching neural networks with variable packet dropouts.

Neural networks : the official journal of the International Neural Network Society Jul 15, 2020
This work focuses on the problem of asynchronous filtering for nonhomogeneous Markov switching neural networks with variable packet dropouts (VPDs). The discrete-time nonhomogeneous Markov process is adopted to depict the modes switching of target pl...
Markov Chains Binomial Distribution Neural Networks, Computer Computer Simulation Probability
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Classification of heart sounds based on the combination of the modified frequency wavelet transform and convolutional neural network.

Medical & biological engineering & computing Jul 7, 2020
We purpose a novel method that combines modified frequency slice wavelet transform (MFSWT) and convolutional neural network (CNN) for classifying normal and abnormal heart sounds. A hidden Markov model is used to find the position of each cardiac cyc...
Cardiovascular Diseases Diagnosis, Computer-Assisted Signal Processing, Computer-Assisted Humans Biomedical Engineering Neural Networks, Computer Markov Chains Heart Sounds Algorithms Wavelet Analysis Phonocardiography Models, Cardiovascular
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Delay-distribution-dependent state estimation for neural networks under stochastic communication protocol with uncertain transition probabilities.

Neural networks : the official journal of the International Neural Network Society Jul 6, 2020
In this paper, the protocol-based remote state estimation problem is considered for a kind of delayed artificial neural networks. The random time-varying delays fall into certain intervals with known probability distributions. For the sake of reducin...
Communication Time Factors Probability Markov Chains Stochastic Processes Uncertainty Neural Networks, Computer
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Deep Learning for Improved Risk Prediction in Surgical Outcomes.

Scientific reports Jun 9, 2020
The Norwood surgical procedure restores functional systemic circulation in neonatal patients with single ventricle congenital heart defects, but this complex procedure carries a high mortality rate. In this study we address the need to provide an acc...
Hospital Mortality Models, Statistical Heart Ventricles Infant Deep Learning Length of Stay Decision Making, Organizational Hypoplastic Left Heart Syndrome Norwood Procedures Markov Chains Risk Monte Carlo Method Humans Neural Networks, Computer Infant, Newborn
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An Application of Random Walk Resampling to Phylogenetic HMM Inference and Learning.

IEEE transactions on nanobioscience May 8, 2020
Statistical resampling methods are widely used for confidence interval placement and as a data perturbation technique for statistical inference and learning. An important assumption of popular resampling methods such as the standard bootstrap is that...
Sequence Alignment Machine Learning Computer Simulation Phylogeny Computational Biology Markov Chains
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GOMCL: a toolkit to cluster, evaluate, and extract non-redundant associations of Gene Ontology-based functions.

BMC bioinformatics Apr 10, 2020
BACKGROUND: Functional enrichment of genes and pathways based on Gene Ontology (GO) has been widely used to describe the results of various -omics analyses. GO terms statistically overrepresented within a set of a large number of genes are typically ...
High-Throughput Screening Assays Plant Roots User-Computer Interface Gene Ontology Multigene Family Arabidopsis Markov Chains
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HMMPred: Accurate Prediction of DNA-Binding Proteins Based on HMM Profiles and XGBoost Feature Selection.

Computational and mathematical methods in medicine Mar 28, 2020
Prediction of DNA-binding proteins (DBPs) has become a popular research topic in protein science due to its crucial role in all aspects of biological activities. Even though considerable efforts have been devoted to developing powerful computational ...
Support Vector Machine Algorithms DNA-Binding Proteins Databases, Protein Humans Amino Acid Sequence Amino Acids ROC Curve Machine Learning Markov Chains Computational Biology
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The Role and Promise of Artificial Intelligence in Medical Toxicology.

Journal of medical toxicology : official journal of the American College of Medical Toxicology Mar 25, 2020
Artificial intelligence (AI) refers to machines or software that process information and interact with the world as understanding beings. Examples of AI in medicine include the automated reading of chest X-rays and the detection of heart dysrhythmias...
Vocabulary, Controlled Psychotropic Drugs Humans Markov Chains Toxicology Big Data Knowledge Bases Neural Networks, Computer Data Mining Artificial Intelligence Deep Learning
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Graph embedding and unsupervised learning predict genomic sub-compartments from HiC chromatin interaction data.

Nature communications Mar 3, 2020
Chromatin interaction studies can reveal how the genome is organized into spatially confined sub-compartments in the nucleus. However, accurately identifying sub-compartments from chromatin interaction data remains a challenge in computational biolog...
Neural Networks, Computer Data Analysis Algorithms Reproducibility of Results Chromatin Genomics Unsupervised Machine Learning Cluster Analysis Epigenome Humans Gene Expression K562 Cells Markov Chains Computer Graphics
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Resilient fault-tolerant anti-synchronization for stochastic delayed reaction-diffusion neural networks with semi-Markov jump parameters.

Neural networks : the official journal of the International Neural Network Society Feb 28, 2020
This paper deals with the anti-synchronization issue for stochastic delayed reaction-diffusion neural networks subject to semi-Markov jump parameters. A resilient fault-tolerant controller is utilized to ensure the anti-synchronization in the presenc...
Markov Chains Humans Stochastic Processes Neural Networks, Computer Diffusion
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