DocumentCode :
253267
Title :
Degree of Disease possibility (DDP): A mining based statistical measuring approach for disease prediction in health care data mining
Author :
Nagavelli, Ramana ; Guru Rao, C.V.
Author_Institution :
Dept. of Comput. Sci. & Eng., Kakatiya Univ., Warangal, India
fYear :
2014
fDate :
9-11 May 2014
Firstpage :
1
Lastpage :
6
Abstract :
We propose a novel mining based statistical analysis approach to predict the scope of a disease by the given patient record. We labeled the proposed measuring process as Degree of Disease possibility. The said model is devising degree of disease possibility threshold (ddpt) and its lower and upper bounds. In regard to predict the ddpt, here we remodeled the HITs algorithm, which is popularly used to derive the hyper link weights of a given website. The experimental results explored in this paper indicating the significance of the proposed model.
Keywords :
Web sites; data mining; diseases; health care; medical information systems; statistical analysis; DDP; HIT algorithm; Web site; ddpt; degree of disease possibility threshold; disease prediction; health care data mining; hyper link weights; mining based statistical measuring approach; patient record; statistical analysis; Computer aided software engineering; Frequency selective surfaces; Performance analysis; Associativity; Disease prediction; HITS algorithm; Health Mining; weighted associative classifiers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Recent Advances and Innovations in Engineering (ICRAIE), 2014
Conference_Location :
Jaipur
Print_ISBN :
978-1-4799-4041-7
Type :
conf
DOI :
10.1109/ICRAIE.2014.6909265
Filename :
6909265
Link To Document :
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