An outcome discovery system to determine mortality factors in primary care facilities

Document Type

Conference Proceeding

Publication Date

12-1-2009

Abstract

This project assembles a virtual team consisting of personnel from the New Jersey Institute of Technology with expertise in the data mining domain and the Saint Barnabas Health Care System with expertise in the medical domain. We apply proven techniques in data and text mining to the problem of hospital mortality. Methodology in outcomes research using data/text mining has typically included Bayesian Networks to include decision trees and rules, regression analysis or Neural Networks/Support Vector Machines to analyze a single disease or condition. We propose to instead analyze the entire spectrum of reasons patients are admitted to a hospital in an effort to discern what chronologies result in good outcomes and which in the worst outcome so as to identify the characteristics to be avoided throughout the spectrum of reasons for admission.

Identifier

74049101497 (Scopus)

ISBN

[9781605588032]

Publication Title

International Conference on Information and Knowledge Management Proceedings

External Full Text Location

https://doi.org/10.1145/1651318.1651341

First Page

95

Last Page

96

This document is currently not available here.

Share

COinS