Title :
Mining Acute Inflammations of urinary system using GAJA2: A new data mining algorithm
Author :
Kooptiwoot, Suwimon
Author_Institution :
Comput. Sci. Program, Suan Sunandha Rajabhat Univ., Bangkok, Thailand
Abstract :
Medical data mining is so challenging. In this paper, we propose a new data mining algorithm called GAJA2, which is a derivation of GAJA [1]. We apply GAJA2 to mine Acute Inflammations data set, a medical data set got from UCI machine learning repository 2009[2]. This data set is about symptoms and diagnosis of two diseases of urinary system which are inflammation of urinary bladder and Nephritis of renal pelvis origin. The results show that knowledge mined by using GAJA2 is very interesting. We compare the results from GAJA2 with GAJA and Rough Set Theory. We found that the results from GAJA2 can be used by the experts in the fields and are very much easier to understand than from GAJA and Rough Set Theory.
Keywords :
data mining; medical computing; rough set theory; Nephritis; UCI machine learning repository; acute inflammation; medical data mining algorithm; medical data set; renal pelvis origin; rough set theory; urinary bladder; urinary system; Artificial neural networks; Classification algorithms; Machine learning; Presses; Acute Inflammations of Urinary System; GAJA2; Medical Data Mining; Nephritis of renal pelvis origin; inflammation of urinary bladder;
Conference_Titel :
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-5537-9
DOI :
10.1109/ICCSIT.2010.5563594