Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/6837
Title: Validation of a novel traditional Chinese medicine pulse diagnostic model using an artificial neural network
Authors: Tang, ACY
Chung, J
Wong, TKS
Keywords: Cancer pain
Issue Date: 2012
Publisher: Hindawi Publishing Corporation
Source: Evidence-based complementary and alternative medicine, 2012, v. 2012, 685094, p. 1-7 How to cite?
Journal: Evidence-based complementary and alternative medicine 
Abstract: In view of lacking a quantifiable traditional Chinese medicine (TCM) pulse diagnostic model, a novel TCM pulse diagnostic model was introduced to quantify the pulse diagnosis. Content validation was performed with a panel of TCM doctors. Criterion validation was tested with essential hypertension. The gold standard was brachial blood pressure measured by a sphygmomanometer. Two hundred and sixty subjects were recruited (139 in the normotensive group and 121 in the hypertensive group). A TCM doctor palpated pulses at left and right cun, guan, and chi points, and quantified pulse qualities according to eight elements (depth, rate, regularity, width, length, smoothness, stiffness, and strength) on a visual analog scale. An artificial neural network was used to develop a pulse diagnostic model differentiating essential hypertension from normotension. Accuracy, specificity, and sensitivity were compared among various diagnostic models. About 80% accuracy was attained among all models. Their specificity and sensitivity varied, ranging from 70% to nearly 90%. It suggested that the novel TCM pulse diagnostic model was valid in terms of its content and diagnostic ability.
URI: http://hdl.handle.net/10397/6837
ISSN: 1741-427X
EISSN: 1741-4288
DOI: 10.1155/2012/685094
Rights: Copyright © 2012 Anson Chui Yan Tang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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