Results 121 to 130 of about 7,662,414 (297)

Hierarchical Bayesian Spatio-Temporal Analysis of Childhood Cancer Trends [PDF]

open access: yes, 2012
In this paper, generalized additive mixed models are constructed for the analysis of geographical and temporal variability of cancer ratios. In this class of models, spatially correlated random effects and temporal components are adopted. Spatio-temporal
Rosychuk, Rhonda J., Torabi, Mahmoud
core   +1 more source

Towards a Compositional Framework for Describing Human Phenotypes

open access: yesAdvanced Science, EarlyView.
The Phenotype Assembly Method (PhenoAM) decomposes phenotype variables into measurable Features and typed Qualifiers, enabling standardized, machine‐readable Phenome Data Elements (PhenoDEs) that preserve measurement context. Applied in the International Human Phenome Project (IHPP), the framework yields 58 371 PhenoDEs and supports component‐level ...
Wanting Hu   +11 more
wiley   +1 more source

Bayesian Learning in Undirected Graphical Models: Approximate MCMC algorithms [PDF]

open access: yes, 2004
Bayesian learning in undirected graphical models—computing posterior distributions over parameters and predictive quantities—is exceptionally difficult.
Murray, Iain   +2 more
core  

Comparing families of dynamic causal models [PDF]

open access: yes, 2010
Mathematical models of scientific data can be formally compared using Bayesian model evidence. Previous applications in the biological sciences have mainly focussed on model selection in which one first selects the model with the highest evidence and ...
Stephan, Klaas E   +46 more
core   +2 more sources

Smart Bioinks for 4D Bioprinting: Requirements, Design, and Applications

open access: yesAdvanced Science, EarlyView.
Smart bioinks empower 4D‐bioprinted constructs to dynamically adapt and remodel in response to stimuli, effectively biomimicking native tissues. Artificial Intelligence (AI) and Machine Learning (ML) play a guiding role in their rational design by optimizing relevant properties.
Shangsi Chen   +11 more
wiley   +1 more source

A Bayesian hierarchical model for longtitudinal data [PDF]

open access: yes, 2010
The paper investigates a Bayesian hierarchical model for the analysis of longitudinal data from a randomized controlled clinical tuberculosis trial. Data for each subject are observed on thirteen time point of occasions of the trial.
Senthilkumar, B   +3 more
core   +1 more source

Functional MXene Inks for Printed Electronics: Chemistry, Rheology, and Devices

open access: yesAdvanced Science, EarlyView.
Functional MXene inks are emerging as building blocks for MXetronics, connecting MXene synthesis, surface functionalization, ink formulation, and advanced printing with device‐level applications. This review maps how composition, stability, rheology, and processability govern printed structures and enable high‐performance sensors, energy‐storage ...
Shahzaib Ali   +6 more
wiley   +1 more source

Bayesian Hierarchical Tobit Models: an application to travel distance analysis

open access: yesIngeniería, 2017
The objective of travel distance models is to better understand travel behavior so that policies can be implemented for reducing travel and with that the externalities of transport such as air pollution, congestion, and crashes.
Jonathan Aguero-Valverde
doaj   +1 more source

Modeling Player Engagement with Bayesian Hierarchical Models

open access: yesProceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2018
Modeling player engagement is a key challenge in games. However, the gameplay signatures of engaged players can be highly context-sensitive, varying based on where the game is used or what population of players is using it. Traditionally, models of player engagement are investigated in a particular context, and it is unclear how ...
Sawyer, Robert   +3 more
openaire   +2 more sources

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