Clinical Decision Support Using OLAP With Data Mining

The healthcare industry collects huge amounts of data which, unfortunately, are not turned into useful information for effective decision making. Decision support systems (DSS) can now use advanced technologies such as On-Line Analytical Processing (OLAP) and data mining to deliver advanced capabilities. This paper presents a prototype clinical decision support system which combines the strengths of both OLAP and data mining. It provides a rich knowledge environment which is not achievable by using OLAP or data mining alone.

[1]  U. M. Feyyad Data mining and knowledge discovery: making sense out of data , 1996 .

[2]  Sunita Sarawagi,et al.  Explaining Differences in Multidimensional Aggregates , 1999, VLDB.

[3]  Peter A. Flach,et al.  Data Mining for Decision Support , 2003 .

[4]  Ralph Kimball,et al.  The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling , 1996 .

[5]  Huigang Liang,et al.  Data Mining for the Health System Pharmacist , 2003 .

[6]  Torben Bach Pedersen,et al.  Multidimensional Database Technology , 2001, Computer.

[7]  Padhraic Smyth,et al.  From Data Mining to Knowledge Discovery in Databases , 1996, AI Mag..

[8]  A. Bouguettaya,et al.  Healthcare data warehousing and quality assurance , 2001 .

[9]  Gang Liu,et al.  DBMiner: a system for data mining in relational databases and data warehouses , 1997, CASCON.

[10]  Timos K. Sellis,et al.  A survey of logical models for OLAP databases , 1999, SGMD.

[11]  Robert S. Craig,et al.  Microsoft Data Warehousing: Building Distributed Decision Support Systems , 1999 .

[12]  Alexander A. Anisimov Review of The data warehouse toolkit: the complete guide to dimensional modeling (2nd edition) by Ralph Kimball, Margy Ross. John Wiley & Sons, Inc. 2002. , 2003, SGMD.

[13]  Usama M. Fayyad,et al.  Data Mining and Knowledge Discovery: Making Sense Out of Data , 1996, IEEE Expert.

[14]  Kanti Bansal,et al.  NEURAL NETWORKS BASED DATA MINING APPLICATIONS FOR MEDICAL INVENTORY PROBLEMS , 1998 .

[15]  Surajit Chaudhuri,et al.  An overview of data warehousing and OLAP technology , 1997, SGMD.

[16]  Usama M. Fayyad,et al.  Data mining and knowledge discovery in databases: implications for scientific databases , 1997, Proceedings. Ninth International Conference on Scientific and Statistical Database Management (Cat. No.97TB100150).

[17]  Philip S. Yu,et al.  Data Mining: An Overview from a Database Perspective , 1996, IEEE Trans. Knowl. Data Eng..

[18]  Daniel E. O'Leary,et al.  Intelligent Executive Information Systems , 1996, IEEE Expert.

[19]  Alan R. Hevner,et al.  Healthcare Data Warehousing and Quality Assurance , 2001, Computer.

[20]  Christer Carlsson,et al.  Past, present, and future of decision support technology , 2002, Decis. Support Syst..

[21]  David F. Lobach,et al.  Medical data mining: knowledge discovery in a clinical data warehouse , 1997, AMIA.

[22]  Petra Perner,et al.  Data Mining - Concepts and Techniques , 2002, Künstliche Intell..

[23]  Kevin C. Desouza,et al.  Data mining in healthcare information systems: case study of a veterans' administration spinal cord injury population , 2003, 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the.

[24]  Surajit Chaudhuri,et al.  Database Technology for Decision Support Systems , 2001, Computer.

[25]  Catherine Blake,et al.  UCI Repository of machine learning databases , 1998 .

[26]  Helen Hasan,et al.  Using OLAP and multidimensional data for decision making , 2001 .

[27]  Jiawei Han,et al.  OLAP Mining: Integration of OLAP with Data Mining , 1997, DS-7.

[28]  George Colliat,et al.  OLAP, relational, and multidimensional database systems , 1996, SGMD.