title: A similarity based learning framework for interim analysis of outcome prediction of acupuncture for neck pain.
abstract: Chronic neck pain is a common morbid disorder in modern society. Acupuncture has been administered for treating chronic pain as an alternative therapy for a long time, with its effectiveness supported by the latest clinical evidence. However, the potential effective difference in different syndrome types is questioned due to the limits of sample size and statistical methods. We applied machine learning methods in an attempt to solve this problem. Through a multi-objective sorting of subjective measurements, outstanding samples are selected to form the base of our kernel-oriented model. With calculation of similarities between the concerned sample and base samples, we are able to make full use of information contained in the known samples, which is especially effective in the case of a small sample set. To tackle the parameters selection problem in similarity learning, we propose an ensemble version of slightly different parameter setting to obtain stronger learning. The experimental result on a real data set shows that compared to some previous well-known methods, the proposed algorithm is capable of discovering the underlying difference among different syndrome types and is feasible for predicting the effective tendency in clinical trials of large samples.
authors.affiliation: School of Information Science, SUN YAT-SEN University, Guangzhou 510000, China. ipx@gdut.edu.cn
authors.forename: Gang
authors.initials: G
authors.lastname: Zhang
authors.affiliation: Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510120, China.
authors.forename: Zhaohui
authors.initials: Z
authors.lastname: Liang
authors.affiliation: School of Information Science, SUN YAT-SEN University, Guangzhou 510275, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Yin
authors.affiliation: Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510120, China.
authors.forename: Wenbin
authors.initials: W
authors.lastname: Fu
authors.affiliation: Guangdong Provincial Academy of Chinese Medical Sciences, Guangzhou 510120, China.
authors.forename: Guo-Zheng
authors.initials: GZ
authors.lastname: Li
mesh_terms: D015670:Acupuncture Therapy; D000465:Algorithms; D001185:Artificial Intelligence; D006801:Humans; D019547:Neck Pain / Q000628:therapy*