AIMC Topic: Markov Chains

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Training forecast to football athletes using Hopfield neural networks based on Markov matrix.

PloS one Jan 1, 2025
This paper proposes a neural network based on the Markov probability transition matrix to predict the training performance of football athletes. Firstly, seven training indicators affecting the training performance are designed by the Event-group tra...
Neural Networks, Computer Forecasting Markov Chains Humans Athletes Soccer Hopfield Neural Networks Football Athletic Performance
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Protocol for evaluating the cost-effectiveness of Mongolia's sugar-sweetened beverages tax using double machine learning.

PloS one Jan 1, 2025
Elevated consumption of sugar-sweetened beverages (SSBs) has been associated with an increase in obesity, type 2 diabetes, and other non-communicable diseases (NCDs), a significant health and economic burden on Mongolia. To address this, the governme...
Humans Machine Learning Adult Male Middle Aged Female Young Adult Mongolia Models, Economic Quality-Adjusted Life Years Taxes Disability-Adjusted Life Years Sugar-Sweetened Beverages Adolescent Cost-Benefit Analysis Obesity Markov Chains
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Mitigating epidemic spread in complex networks based on deep reinforcement learning.

Chaos (Woodbury, N.Y.) Dec 1, 2024
Complex networks are susceptible to contagious cascades, underscoring the urgency for effective epidemic mitigation strategies. While physical quarantine is a proven mitigation measure for mitigation, it can lead to substantial economic repercussions...
Epidemics Quarantine Markov Chains Humans Computer Simulation Deep Learning Algorithms
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Tiberius: end-to-end deep learning with an HMM for gene prediction.

Bioinformatics (Oxford, England) Nov 28, 2024
MOTIVATION: For more than 25 years, learning-based eukaryotic gene predictors were driven by hidden Markov models (HMMs), which were directly inputted a DNA sequence. Recently, Holst et al. demonstrated with their program Helixer that the accuracy of...
Software Algorithms Deep Learning Humans Markov Chains Animals Computational Biology Genome, Human
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Comparing machine learning and deep learning models to predict cognition progression in Parkinson's disease.

Clinical and translational science Nov 1, 2024
Cognitive decline in Parkinson's disease (PD) varies widely. While models to predict cognitive progression exist, comparing traditional probabilistic models to deep learning methods remains understudied. This study compares sequential modeling techni...
Markov Chains Cognition Parkinson Disease Cognitive Dysfunction Dementia Aged Male Disease Progression Deep Learning Middle Aged Humans Machine Learning Female
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Method for remaining useful life prediction of rolling bearings based on deep reinforcement learning.

The Review of scientific instruments Sep 1, 2024
In contemporary industrial systems, the prediction of remaining useful life (RUL) is recognized as a valuable maintenance strategy for health management due to its ability to monitor equipment operational status in real time and ensure the safety of ...
Markov Chains Algorithms Deep Learning Neural Networks, Computer
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IsoFrog: a reversible jump Markov Chain Monte Carlo feature selection-based method for predicting isoform functions.

Bioinformatics (Oxford, England) Sep 2, 2023
MOTIVATION: A single gene may yield several isoforms with different functions through alternative splicing. Continuous efforts are devoted to developing machine-learning methods to predict isoform functions. However, existing methods do not consider ...
Markov Chains Monte Carlo Method Machine Learning Protein Isoforms Alternative Splicing
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Distributed nonsynchronous event-triggered state estimation of genetic regulatory networks with hidden Markovian jumping parameters.

Mathematical biosciences and engineering : MBE Sep 20, 2022
In this paper, the distributed state estimation problem of genetic regulatory networks (GRNs) with hidden Markovian jumping parameters (HMJPs) is explored. Furthermore, in order to improve the communication efficiency among state estimation sensors, ...
Proteins Markov Chains Neural Networks, Computer Communication Gene Regulatory Networks
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Hierarchical reinforcement learning for automatic disease diagnosis.

Bioinformatics (Oxford, England) Aug 10, 2022
MOTIVATION: Disease diagnosis-oriented dialog system models the interactive consultation procedure as the Markov decision process, and reinforcement learning algorithms are used to solve the problem. Existing approaches usually employ a flat policy s...
Algorithms Markov Chains Deep Learning
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GraphVAMPNet, using graph neural networks and variational approach to Markov processes for dynamical modeling of biomolecules.

The Journal of chemical physics May 14, 2022
Finding a low dimensional representation of data from long-timescale trajectories of biomolecular processes, such as protein folding or ligand-receptor binding, is of fundamental importance, and kinetic models, such as Markov modeling, have proven us...
Protein Folding Molecular Dynamics Simulation Markov Chains Neural Networks, Computer Kinetics
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