Intelligent ZHENG Classification of Hypertension Depending on ML-kNN and Information Fusion

Hypertension is one of the major causes of heart cerebrovascular diseases. With a good accumulation of hypertension clinical data on hand, research on hypertension's ZHENG differentiation is an important and attractive topic, as Traditional Chinese Medicine (TCM) lies primarily in “treatment based on ZHENG differentiation.” From the view of data mining, ZHENG differentiation is modeled as a classification problem. In this paper, ML-kNN—a multilabel learning model—is used as the classification model for hypertension. Feature-level information fusion is also used for further utilization of all information. Experiment results show that ML-kNN can model the hypertension's ZHENG differentiation well. Information fusion helps improve models' performance.

[1]  Arun Ross,et al.  Information fusion in biometrics , 2003, Pattern Recognit. Lett..

[2]  A. Ross,et al.  Level Fusion Using Hand and Face Biometrics , 2005 .

[3]  Arun Ross,et al.  Feature level fusion of hand and face biometrics , 2005, SPIE Defense + Commercial Sensing.

[4]  Zhi-Hua Zhou,et al.  ML-KNN: A lazy learning approach to multi-label learning , 2007, Pattern Recognit..

[5]  Jack Y. Yang,et al.  Feature selection for gene function prediction using multi-labelled lazy learning , 2008, Int. J. Funct. Informatics Pers. Medicine.

[6]  Jack Y. Yang,et al.  Feature selection for semi-supervised multi-label learning with application to gene function analysis , 2010, BCB '10.

[7]  Grigorios Tsoumakas,et al.  Mining Multi-label Data , 2010, Data Mining and Knowledge Discovery Handbook.

[8]  Guozheng Li,et al.  Modelling of inquiry diagnosis for coronary heart disease in traditional Chinese medicine by using multi-label learning , 2010, BMC complementary and alternative medicine.

[9]  Yonghong Peng,et al.  Text mining for traditional Chinese medical knowledge discovery: A survey , 2010, J. Biomed. Informatics.

[10]  Guangwen Yang,et al.  Optimizing write operation on replica in data grid , 2011, Science China Information Sciences.

[11]  Yiqin Wang.  Progress and prospect of objectivity study on four diagnostic methods in Traditional Chinese Medicine , 2010, 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW).

[12]  Renan Oliveira Vaz-de-Melo,et al.  Hypertensive crisis: clinical–epidemiological profile , 2011, Hypertension Research.

[13]  Junbin Gao,et al.  A novel approach in discovering significant interactions from TCM patient prescription data , 2011, Int. J. Data Min. Bioinform..

[14]  Yiqin Wang,et al.  Symptom selection for multi-label data of inquiry diagnosis in traditional Chinese medicine , 2013, Science China Information Sciences.