The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS
Transactions ID Number: 29-738
Full Name: Nittaya Kerdprasop
Position: Associate Professor
Age: ON
Sex: Female
Address: School of Computer Engineering, Suranaree University of Technology, 111 University Avenue, Nakhon Ratchasima 30000
Country: THAILAND
Tel: (0)44-22-4432
Tel prefix: 66
Fax: +66-44-224602
E-mail address: nittaya.k@gmail.com
Other E-mails: nittaya@sut.ac.th
Title of the Paper: Knowledge induction from medical databases with higher-order programming
Authors as they appear in the Paper: Nittaya Kerdprasop and Kittisak Kerdprasop
Email addresses of all the authors: nittaya.k@gmail.com,kittisakThailand@gmail.com
Number of paper pages: 10
Abstract: Medical data mining is an emerging area of computational intelligence applied to automatically analyze patients' records aiming at the discovery of new knowledge potentially useful for medical decision making. Induced knowledge is anticipated not only to increase accurate diagnosis and successful disease treatment, but also to enhance safety by reducing medication-related errors. Modern healthcare organizations regularly generate huge amount of electronic data that could be used as a valuable resource for knowledge induction to support decision-making of medical practitioners. Unfortunately, a domain-specific decision support system that provides a suite of customized and flexible tools to efficiently induce knowledge from medical databases with representational heterogeneity does not currently exist. We, thus, design and develop a medical decision support system based on a powerful logic programming framework. The proposed system includes a knowledge induction com!
ponent to induce knowledge from clinical data repositories and the induced knowledge can also be deployed to pre-treatment data from other sources. The implementation of knowledge induction engine has been presented to express the power of higher-order programming of logic-based language. The flexibility of our mining engine is obtained through the pattern matching and meta-programming facilities provided by logic-based language.
Keywords: Medical decision making, Medical informatics, Logic-based knowledge induction, Higher-order programming
EXTENSION of the file: .pdf
Special (Invited) Session: Medical knowledge induction with higher-order Horn clauses and meta-programming
Organizer of the Session: 617-247
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