Ranking sociodemographic, health behavior, prevention, and environmental factors in predicting neighborhood cardiovascular health: A Bayesian machine learning approach

Preventive Medicine ◽

10.1016/j.ypmed.2020.106240 ◽

2020 ◽

Vol 141 ◽

pp. 106240 ◽

Author(s):

Liangyuan Hu ◽

Bian Liu ◽

Yan Li

Keyword(s):

Machine Learning ◽

Environmental Factors ◽

Health Behavior ◽

Cardiovascular Health ◽

Learning Approach ◽

Machine Learning Approach ◽

Bayesian Machine Learning

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Mobile Collaborative Spectrum Sensing for Heterogeneous Networks: A Bayesian Machine Learning Approach

IEEE Transactions on Signal Processing ◽

10.1109/tsp.2018.2870379 ◽

2018 ◽

Vol 66 (21) ◽

pp. 5634-5647 ◽

Author(s):

Yizhen Xu ◽

Peng Cheng ◽

Zhuo Chen ◽

Yonghui Li ◽

Branka Vucetic

Keyword(s):

Machine Learning ◽

Spectrum Sensing ◽

Heterogeneous Networks ◽

Learning Approach ◽

Collaborative Spectrum Sensing ◽

Machine Learning Approach ◽

Bayesian Machine Learning

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Machine Learning Approach to Identifying Key Environmental Factors for Airfield Asphalt Pavement Performance

Airfield and Highway Pavements 2021 ◽

10.1061/9780784483503.032 ◽

2021 ◽

Author(s):

A. Z. Ashtiani ◽

S. Murrell ◽

D. R. Brill

Keyword(s):

Machine Learning ◽

Environmental Factors ◽

Asphalt Pavement ◽

Pavement Performance ◽

Learning Approach ◽

Machine Learning Approach

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A Bayesian Machine Learning Approach for Efficient Integrity Management of Steel Lazy Wave Risers

10.1115/1.0000856v ◽

2021 ◽

Author(s):

Seyed Rasoul Hejazi ◽

Andrew Grime ◽

Mark Randolph ◽

Mike Efthymiou

Keyword(s):

Machine Learning ◽

Learning Approach ◽

Machine Learning Approach ◽

Integrity Management ◽

Bayesian Machine Learning

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A Bayesian Machine Learning Approach for Smart City

International Journal for Research in Applied Science and Engineering Technology ◽

10.22214/ijraset.2021.39195 ◽

2021 ◽

Vol 9 (12) ◽

pp. 796-816

Author(s):

Ravi Prakash Malviya

Keyword(s):

Machine Learning ◽

Learning Approach ◽

Machine Learning Approach ◽

Bayesian Machine Learning

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Bayesian Machine Learning Approach to the Quantification of Uncertainties on Ab Initio Potential Energy Surfaces

The Journal of Physical Chemistry A ◽

10.1021/acs.jpca.0c02395 ◽

2020 ◽

Vol 124 (25) ◽

pp. 5129-5146 ◽

Author(s):

S. Venturi ◽

R. L. Jaffe ◽

M. Panesi

Keyword(s):

Machine Learning ◽

Potential Energy ◽

Ab Initio ◽

Potential Energy Surfaces ◽

Learning Approach ◽

Machine Learning Approach ◽

Energy Surfaces ◽

Bayesian Machine Learning

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The Information Content of Forward-Looking Statements in Corporate Filings-A Naïve Bayesian Machine Learning Approach

Journal of Accounting Research ◽

10.1111/j.1475-679x.2010.00382.x ◽

2010 ◽

Vol 48 (5) ◽

pp. 1049-1102 ◽

Author(s):

FENG LI

Keyword(s):

Machine Learning ◽

Information Content ◽

Learning Approach ◽

Naive Bayesian ◽

Naïve Bayesian ◽

Machine Learning Approach ◽

Bayesian Machine Learning ◽

Forward Looking

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Neighborhood-level stroke and its neighborhood-level determinants: a Bayesian machine learning approach

ISEE Conference Abstracts ◽

10.1289/isee.2020.virtual.p-0168 ◽

2020 ◽

Vol 2020 (1) ◽

Author(s):

L. Hu ◽

B. Liu ◽

J. Ji ◽

Y. Li

Keyword(s):

Machine Learning ◽

Learning Approach ◽

Machine Learning Approach ◽

Bayesian Machine Learning ◽

Neighborhood Level

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Identifying predictors of cancer prevalence at the neighborhood level in the United States: A Bayesian machine learning approach

ISEE Conference Abstracts ◽

10.1289/isee.2021.p-284 ◽

2021 ◽

Vol 2021 (1) ◽

Author(s):

Li Niu ◽

Liangyuan Hu ◽

Yan Li ◽

Bian Liu

Keyword(s):

United States ◽

Machine Learning ◽

The United States ◽

Learning Approach ◽

Cancer Prevalence ◽

Machine Learning Approach ◽

Bayesian Machine Learning ◽

Neighborhood Level

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Finding patterns in subsurface using Bayesian machine learning approach

Underground Space ◽

10.1016/j.undsp.2018.10.006 ◽

2020 ◽

Vol 5 (1) ◽

pp. 84-92 ◽

Author(s):

Hui Wang

Keyword(s):

Machine Learning ◽

Learning Approach ◽

Machine Learning Approach ◽

Bayesian Machine Learning

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Evaluating complex relationships between ecological indicators and environmental factors in the Baltic Sea: A machine learning approach

Ecological Indicators ◽

10.1016/j.ecolind.2018.12.053 ◽

2019 ◽

Vol 101 ◽

pp. 117-125 ◽

Author(s):

Annukka Lehikoinen ◽

Jens Olsson ◽

Lena Bergström ◽

Ulf Bergström ◽

Andreas Bryhn ◽

...

Keyword(s):

Machine Learning ◽

Environmental Factors ◽

Ecological Indicators ◽

Learning Approach ◽

The Baltic Sea ◽

Machine Learning Approach ◽

Complex Relationships ◽

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