Title

Learning Conditional Probabilities for Dynamic Influence Structures in Medical Decision Models

Publication Type

Conference Proceeding Article

Publication Date

10-1997

Abstract

Based on the DynaMoL (a Dynamic decision Modeling Language) framework, we examine the critical issues in automated learning of numerical parameters from large medical databases; present a Bayesian method for learning conditional probabilities from data; analyze how to elicit prior probabilities from the domain expert; and examine several important issues on pre-processing raw data for application in dynamic decision modeling.

Discipline

Artificial Intelligence and Robotics | Computer Sciences | Medicine and Health Sciences

Research Areas

Intelligent Systems and Decision Analytics

Publication

Proceedings of the 1997 American Medical Informatics Association Annual Fall Symposium: October 25-29, Nashville, TN

First Page

848

Last Page

848

Publisher

Hanley and Belfus

City or Country

Philadelphia, PA

Additional URL

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2233501/

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