Results 31 to 40 of about 387,199 (302)

Identifying risk factors of developing type 2 diabetes from an adult population with initial prediabetes using a Bayesian network

open access: yesFrontiers in Public Health, 2023
BackgroundIt is known that people with prediabetes increase their risk of developing type 2 diabetes (T2D), which constitutes a global public health concern, and it is associated with other diseases such as cardiovascular disease.MethodsThis study aimed ...
Pilar Fuster-Parra   +11 more
doaj   +1 more source

The Markov blanket trick: On the scope of the free energy principle and active inference.

open access: yesPhysics of Life Reviews, 2021
The free energy principle (FEP) has been presented as a unified brain theory, as a general principle for the self-organization of biological systems, and most recently as a principle for a theory of every thing.
Vicente Raja   +4 more
semanticscholar   +1 more source

Directed acyclic graphs and causal thinking in clinical risk prediction modeling

open access: yesBMC Medical Research Methodology, 2020
Background In epidemiology, causal inference and prediction modeling methodologies have been historically distinct. Directed Acyclic Graphs (DAGs) are used to model a priori causal assumptions and inform variable selection strategies for causal questions.
Marco Piccininni   +3 more
doaj   +1 more source

A hybrid algorithm for Bayesian network structure learning with application to multi-label learning [PDF]

open access: yes, 2014
We present a novel hybrid algorithm for Bayesian network structure learning, called H2PC. It first reconstructs the skeleton of a Bayesian network and then performs a Bayesian-scoring greedy hill-climbing search to orient the edges.
Aussem, Alex   +2 more
core   +6 more sources

Critique of: “A Parallel Framework for Constraint-Based Bayesian Network Learning via Markov Blanket Discovery” by SCC Team From UC San Diego

open access: yesIEEE Transactions on Parallel and Distributed Systems, 2023
Bayesian networks (BNs) have become popular in recent years to describe natural phenomena in situations where causal linkages are important to understand. In order to get around the inherent non-tractability of learning BNs, Srivastava et al.
Aruna K. Gupta   +12 more
semanticscholar   +1 more source

A Technical Critique of Some Parts of the Free Energy Principle

open access: yesEntropy, 2021
We summarize the original formulation of the free energy principle and highlight some technical issues. We discuss how these issues affect related results involving generalised coordinates and, where appropriate, mention consequences for and reveal, up ...
Martin Biehl   +2 more
doaj   +1 more source

Online Feature Selection for Streaming Features Using Self-Adaption Sliding-Window Sampling

open access: yesIEEE Access, 2019
In recent years, online feature selection has been a research topic on streaming feature mining, as it can reduce the dimensionality of the streaming features by removing the irrelevant and redundant features in real time.
Dianlong You   +6 more
doaj   +1 more source

An Active Inference Account of Touch and Verbal Communication in Therapy

open access: yesFrontiers in Psychology, 2022
This paper offers theoretical explanations for why “guided touch” or manual touch with verbal communication can be an effective way of treating the body (e.g., chronic pain) and the mind (e.g., emotional disorders).
Joohan Kim   +5 more
doaj   +1 more source

Where there is life there is mind: In support of a strong life-mind continuity thesis [PDF]

open access: yes, 2017
This paper considers questions about continuity and discontinuity between life and mind. It begins by examining such questions from the perspective of the free energy principle (FEP).
Froese, Tom, Kirchhoff, Michael David
core   +2 more sources

Two generalizations of Markov blankets

open access: yesCoRR, 2019
In a probabilistic graphical model on a set of variables $V$, the Markov blanket of a random vector $B$ is the minimal set of variables conditioned to which $B$ is independent from the remaining of the variables $V \backslash B$. We generalize Markov blankets to study how a set $C$ of variables of interest depends on~$B$.
Victor Cohen, Axel Parmentier
openaire   +2 more sources

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