A framework for an Intelligent Decision Support System (IDSS), including a data mining methodology, for fetal-maternal clinical practice and research

Abstract

Existing patient medical records are a rich data source with a potential to support clinical research. Fragmentation of data across disparate medical database inhibits the use of these existing datasets. Overcoming such disjointedness is possible through the use of a data warehouse. Once the data is cleansed, transformed, and stored within the data warehouse it is possible to turn attention to the exploration of the medical datasets. Exploratory and confirmatory Data Mining Tools are well suited to such activities. This thesis concerned with: demonstrating parallels between scientific method and CRISP-DM; extending CRISP-DM for use with medical datasets; and proposal of the supporting Intelligent Decision Support System framework. This research has been undertaken using a fetal-maternal case study.

Date of Award	2006
Original language	English