The proposed model nodes include Condition (latent), Diagnosis, History, Age, Sex, Structure and Function, Gait Mechanics, Mobility, Energy, and Quality-of-Life. Extensive details of proposed nodes are found in the text. Descriptions of the paths are found in S1 Appendix. A full implementation of the model (Rmarkdown file) and a de-identified dataset can be found in the S1 File.</p
Ascribing causality amounts to determining what elements in a sequence of reported facts can be rela...
Introduction Reasoning in terms of cause and effect is a strategy that arises in many tasks. For ex...
Causal Networks have recently received much attention in Al, and have been used in many areas as a k...
The main aim was to discover more about how causal models can be used to analyse the progression of ...
The objective of this paper is to present a method for the computer representation of empirically de...
Following a long history of informal use in path analysis, causal diagrams (graphical causal models)...
Abstract: From their inception, causal systems models (more commonly known as structural-equations m...
We address the problem of causal discovery from data, making use of the recently proposed causal mod...
This compressed folder contains the files necessary to generate the model and output from this manus...
⊳ So far: graphs as representation of probabilistic structure ∙ Dependencies and independencies of r...
The drive to understand the laws that govern the universe and ourselves in order to expand our view ...
Abstract Methods of diagrammatic modelling have been greatly developed in the past two decades. Outs...
Contains fulltext : 83455.pdf (preprint version ) (Open Access)PGM-201
The issue of confounding, and the bias it can induce, is a key concern in epidemiology, and yet ther...
Contains fulltext : 201134.pdf (publisher's version ) (Open Access)Radboud Univers...
Ascribing causality amounts to determining what elements in a sequence of reported facts can be rela...
Introduction Reasoning in terms of cause and effect is a strategy that arises in many tasks. For ex...
Causal Networks have recently received much attention in Al, and have been used in many areas as a k...
The main aim was to discover more about how causal models can be used to analyse the progression of ...
The objective of this paper is to present a method for the computer representation of empirically de...
Following a long history of informal use in path analysis, causal diagrams (graphical causal models)...
Abstract: From their inception, causal systems models (more commonly known as structural-equations m...
We address the problem of causal discovery from data, making use of the recently proposed causal mod...
This compressed folder contains the files necessary to generate the model and output from this manus...
⊳ So far: graphs as representation of probabilistic structure ∙ Dependencies and independencies of r...
The drive to understand the laws that govern the universe and ourselves in order to expand our view ...
Abstract Methods of diagrammatic modelling have been greatly developed in the past two decades. Outs...
Contains fulltext : 83455.pdf (preprint version ) (Open Access)PGM-201
The issue of confounding, and the bias it can induce, is a key concern in epidemiology, and yet ther...
Contains fulltext : 201134.pdf (publisher's version ) (Open Access)Radboud Univers...
Ascribing causality amounts to determining what elements in a sequence of reported facts can be rela...
Introduction Reasoning in terms of cause and effect is a strategy that arises in many tasks. For ex...
Causal Networks have recently received much attention in Al, and have been used in many areas as a k...