Mining Clinical Data: Selecting Decision Support Algorithm for the MET-AP System

We have developed an algorithm for triaging acute pediatric abdominal pain in the Emergency Department using the discovery-driven approach. This algorithm is embedded into the MET-AP (Mobile Emergency Triage - Abdominal Pain) system – a clinical decision support system that assists physicians in making emergency triage decisions. In this paper we describe experimental evaluation of several data mining methods (inductive learning, case-based reasoning and Bayesian reasoning) and results leading to the selection of the rule-based algorithm.

• Type: Conference
• Year: 2005
• Where: AIME
• Authors: Jerzy Blaszczynski, Ken Farion, Wojtek Michalowski, Szymon Wilk, Steven Rubin, Dawid Weiss
• Keywords: Abdominal Pain, AIME 2005, Artificial Intelligence, Emergency Triage, Mobile Emergency Triage