Gait Type Analysis Using Dynamic Bayesian Networks [PDF]
Sensors, 2018 This paper focuses on gait abnormality type identification—specifically, recognizing antalgic gait. Through experimentation, we demonstrate that detecting an individual’s gait type is a viable biometric that can be used along with other ...
Patrick Kozlow +2 more
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Dynamic Bayesian Networks for Integrating Multi-omics Time Series Microbiome Data [PDF]
mSystems, 2021 A key challenge in the analysis of longitudinal microbiome data is the inference of temporal interactions between microbial taxa, their genes, the metabolites that they consume and produce, and host genes.
Daniel Ruiz-Perez +6 more
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Dynamic Bayesian Networks for Context-Aware Fall Risk Assessment [PDF]
Sensors, 2014 Fall incidents among the elderly often occur in the home and can cause serious injuries affecting their independent living. This paper presents an approach where data from wearable sensors integrated in a smart home environment is combined using a ...
Gregory Koshmak +2 more
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Polynomial-Time Algorithm for Learning Optimal BFS-Consistent Dynamic Bayesian Networks [PDF]
Entropy, 2018 Dynamic Bayesian networks (DBN) are powerful probabilistic representations that model stochastic processes. They consist of a prior network, representing the distribution over the initial variables, and a set of transition networks, representing the ...
Margarida Sousa, Alexandra M. Carvalho
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Forecasting Subjective Cognitive Decline: AI Approach Using Dynamic Bayesian Networks [PDF]
Journal of Medical Internet ResearchBackgroundSeveral potentially modifiable risk factors are associated with subjective cognitive decline (SCD). However, developmental patterns of these risk factors have not been used before to forecast later SCD.
Antti Etholén +7 more
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Dynamic Bayesian Networks, Elicitation, and Data Embedding for Secure Environments [PDF]
EntropySerious crime modelling typically needs to be undertaken securely behind a firewall where police knowledge and capabilities remain undisclosed. Data informing an ongoing incident are often sparse; a large proportion of relevant data only come to light ...
Kieran Drury, Jim Q. Smith
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Degradation model constructed with the aid of dynamic Bayesian networks
Cogent Engineering, 2017 This paper develops a generic degradation model based on Dynamic Bayesian Networks (DBN) which predicts the condition of a technical system. Besides handling bi-directional reasoning, a major benefit of this degradation model using a DBN is its ability ...
Anselm Lorenzoni +2 more
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Discovering gene regulatory networks of multiple phenotypic groups using dynamic Bayesian networks [PDF]
Briefings in Bioinformatics, 2022 Polina Suter +2 more
exaly +2 more sources
Survey of Research on Non-homogeneous Gene Regulatory Network Models [PDF]
Jisuanji kexue yu tansuo, 2023 In the field of bioinformatics, the construction of gene regulatory networks is crucial. In recent years, non-homogeneous dynamic Bayesian networks have become a common modeling tool for learning gene regulatory networks from gene expression time-series ...
ZHANG Qianqian, HU Chunling, ZHANG Jiayao, LI Dawei, SHAO Mingyi
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Towards an Assembly Support System with Dynamic Bayesian Network
Applied Sciences, 2022 Due to the new technological advancements and the adoption of Industry 4.0 concepts, the manufacturing industry is now, more than ever, in a continuous transformation.
Stefan-Alexandru Precup +4 more
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