TY - GEN
T1 - A study of complication identification based on weighted association rule mining
AU - Yan, Zhijun
AU - Liu, Kai
AU - Xing, Meiming
AU - Wang, Tianmei
AU - Sun, Baowen
N1 - Publisher Copyright:
© IFIP International Federation for Information Processing 2016.
PY - 2016
Y1 - 2016
N2 - With the fast development of big data technology, data mining algorithms are widely used to process the medical data and support clinical decision-making. In this paper, a new method is proposed to mine the disease association rule and predict the possible complications. The concept of disease concurrent weight is proposed and Back Propagation (BP) neural network model is applied to calculate the disease concurrent weight. Adopting the weighted association rule mining algorithm, diseases complication association rule are derived, which can help to remind doctors about patients’ potential complications. The empirical evaluation using hospital patients’ medical information shows that the proposed method is more effective than two baseline methods.
AB - With the fast development of big data technology, data mining algorithms are widely used to process the medical data and support clinical decision-making. In this paper, a new method is proposed to mine the disease association rule and predict the possible complications. The concept of disease concurrent weight is proposed and Back Propagation (BP) neural network model is applied to calculate the disease concurrent weight. Adopting the weighted association rule mining algorithm, diseases complication association rule are derived, which can help to remind doctors about patients’ potential complications. The empirical evaluation using hospital patients’ medical information shows that the proposed method is more effective than two baseline methods.
KW - Complications
KW - Data mining
KW - Neural network
KW - Weighted association rule
UR - http://www.scopus.com/inward/record.url?scp=84979603391&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-42102-5_17
DO - 10.1007/978-3-319-42102-5_17
M3 - Conference contribution
AN - SCOPUS:84979603391
SN - 9783319421018
T3 - IFIP Advances in Information and Communication Technology
SP - 149
EP - 158
BT - Socially Aware Organisations and Technologies
A2 - de Almeida Neris, Vânia Paula
A2 - Baranauskas, Maria Cecilia Calani
A2 - Bonacin, Rodrigo
A2 - Liu, Kecheng
A2 - Sun, Lily
A2 - Nakata, Keiichi
PB - Springer New York LLC
T2 - 17th IFIP WG 8.1 International Conference on Informatics and Semiotics in Organisations, ICISO 2016
Y2 - 1 August 2016 through 3 August 2016
ER -