Operational protocols are a valuable means for quality control. However, de
veloping operational protocols is a highly complex and costly task. We pres
ent an integrated approach involving both intelligent data analysis and kno
wledge acquisition from experts that support the development of operational
protocols. The aim is to ensure high quality standards for the protocol th
rough empirical validation during the development, as well as lower develop
ment cost through the use of machine learning and statistical techniques. W
e demonstrate our approach of integrating expert knowledge with data driven
techniques based on our effort to develop an operational protocol for the
hemodynamic system. (C) 2000 Elsevier Science B.V. All rights reserved.