From complex questionnaire and interviewing data to intelligent Bayesian network models for medical decision support.

ABSTRACT:

Objectives

(1) To develop a rigorous and repeatable method for building effective Bayesian network (BN) models for medical decision support from complex, unstructured and incomplete patient questionnaires and interviews that inevitably contain examples of repetitive, redundant and contradictory responses; (2) To exploit expert knowledge in the BN development since further data acquisition is usually not possible; (3) To ensure the BN model can be used for interventional analysis; (4) To demonstrate why using data alone to learn the model structure and parameters is often unsatisfactory even when extensive data is available.

Method

The method is based on applying a range of recent BN developments targeted at helping experts build BNs given limited data. While most of the comp

SUBMITTER: Constantinou AC 

PROVIDER: S-EPMC4839499 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature