Perreault, L.E. and Metzger, J.B. (1999) A pragmatic framework for understanding clinical decision support. In: Middleton, B., Ed., Clinical decision support systems. Journal of Healthcare Information Management, 13(2), 5-21.

has been cited by the following article:

• TITLE: Advanced decision support for complex clinical decisions

  AUTHORS: Brain Keltch, Yuan Lin, Coskun Bayrak

  KEYWORDS: Fibrosis; Clinical Decision Support; Decision Tree; Neural Network

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.3 No.5, May 27, 2010

  ABSTRACT: A Physician’s decision-making skills are directly related to the patient’s positive outcomes. Therefore, a wealth of medical knowledge and clinical experience are key assets for a physician to have. The goal here is to use historical clinical data and relationships processed by Artificial Intelligence (AI) techniques to aid physicians in their decision making process. Presenting this information in a Clinical Decision Support System (CDSS) is an effective means to consolidate decision results. The CDSS provides a large number of medical support functions to help clinicians make the most reasonable diagnosis and choose the best treatment measures. Initial results have shown great promise in accurately predicting Fibrosis Stage in Hepatitis patients. Utilizing this tool could mitigate the need for some liver biopsies in the more than 170 million Hepatitis patients worldwide. The prototype is extendable to accommodate additional techniques (for example genetic algorithms and logistics regression) and additional medical domain solutions (for example HIV/AIDS).