Technology to support Bayesian Belief Network
construction and inference
| developed by |
clinical domains |
keywords |
| Norsys Software Corp., |
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Bayesian Networks; Bayesian net; belief net; probability;
expert system software;
influence diagram; probabilistic modelling;
simulation software; data mining; machine learning |
| status |
access demonstrator |
| Commercial product. Demonstrator version available. |
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| description |
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Norsys describes Netica™ as "the world's most widely used Bayesian network development software".
"Netica is a powerful, easy-to-use, complete program for working with belief networks and influence diagrams. It has an intuitive and smooth user interface for drawing the networks, and the relationships between variables may be entered as individual probabilities, in the form of equations, or learned from data files... "
Some features
"Generates presentation quality graphics which can be incorporated into other documents.
Compiles belief (Bayesian) networks into a junction tree of cliques for fast probabilistic reasoning.
Extensive on-screen help and a detailed printed manual.
Can test the performance of a network using a file of cases.
Can find optimal decisions for sequential decision problems (i.e., later decisions are dependent on the results of earlier ones).
Can solve influence diagrams efficiently by using clique trees.
Can learn probabilistic relations from data.
Provides easy graphical editing of belief networks and influence diagrams, including:
cut / paste / duplicate nodes without loosing their probabilistic relation ...
Allows the entry of probabilistic relations by equation, with an extensive built-in library of probabilistic functions and other mathematical functions.
Supports disconnected links, which makes possible libraries of probabilistic relationships.
Accepts likelihood findings (i.e., virtual evidence), and findings of the form that some variable is not in some state.
Supports documentation and tracking of every node and network (with comments, titles, author, when last changed, etc.)
Can work hand-in-hand with the Netica API product (for example, sharing the same files)... Netica APIs are a family of powerful Bayesian Network toolkits that allow you to build your own Bayesian belief networks and influence diagrams, do probabilistic inference, learn nets from data, modify nets, and save and restore nets. There are currently three APIs to choose from, while a fourth is under development.... "
[Norsys Corp.]
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| references |
| Bothtner U, Milne SE, Kenny GN, Georgieff M, Schraag S.
Bayesian probabilistic network modeling of remifentanil and propofol interaction on wakeup time after closed-loop controlled anesthesia.
J Clin Monit Comput. 2002 Jan;17(1):31-6.
[PubMed]
[]
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" OBJECTIVE: Until now, the knowledge of combining anesthetics to obtain an adequate level of anesthesia and to economize wakeup time has been empirical and difficult to represent in quantitative models. Since there is no reason to expect that the effect of non-opioid and opioid anesthetics can be modeled in a simple linear manner, the use of a new computational approach with Bayesian belief network software is demonstrated. METHODS: A data set from a pharmacodynamic study was used where remifentanil was randomly given in three fixed target concentrations (2, 4, and 8 ng/ml) to 62 subjects. Target concentrations of propofol were controlled according to the closed-loop system feedback of the auditory evoked potential index to render modeling unbiased by the level of anesthesia. Time to open eyes was measured to represent wakeup time after surgery. The NETICA version 1.37 software was used on a personal computer for network building, validation, and prediction. RESULTS: After the learning phase, the network was used to generate a series of random cases whose probability distribution matches that of the compiled network. The sampling algorithms used are precise, so that the frequencies of the simulated cases will exactly approach the probabilities of the network and that of the data learned. The graphical display of the predicted wakeup time shows less variability but a more complex interaction pattern than with the unadjusted original data. CONCLUSIONS: Model building and evaluation with Bayesian networks does not depend on underlying linear relationships. Bayesian relationships represent true features of the represented data sample. Data may be sparse, uncertain, stochastic, or imprecise. Multiple platform software that is easy to use is increasingly available. Bayesian networks promise to be versatile tools for building valid, nonlinear, predictive instruments to further gain insight into the complex interaction of anesthetics." |
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| contact |
links |
Norsys Software Corp.
3512 West 23rd Avenue
Vancouver, BC,
CANADA
V6S 1K5
Web: contact
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| acknowledgements |
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Entry on OpenClinical: 30 August 2004
Last main update: 30 August 2004
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Netica
The demonstration version of Netica Application is full-featured but allows only limited model size. This version can be freely used, subject to agreement with the Norsys License Agreement for Netica Application.
Versions of Netica API are available for many platforms (including Microsoft Windows, Linux, Sun Sparc, Mac ...).