|
| An approach to TCM evaluate the efficacy of ARDS based on weighted mixed regression model |
| Hits 2205 Download times 114 Received:September 17, 2016 |
| View Full Text View/Add Comment Download reader |
| DOI
10.11656/j.issn.1673-9043.2016.06.03 |
| Key Words
acute respiratory distress syndrome;evaluation method of curative effect;individualized diagnosis and treatment;matrix analysis;weighted mixed regression model |
| Author Name | Affiliation | E-mail | | WANG Hai-ying | Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300150, China | | | LIU En-shun | Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin 300150, China | hellotcm@126.com | | HE Yi | Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China | | | ZHANG He-ming | Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China | |
|
| Abstract
|
| Acute respiratory distress syndrome(ARDS) is a common clinical critical disease,of which the TCM treatment showed a positive effect in the treatment.However,the lack of reasonable evaluation method leas to the masked and questioned effect,which is seriously affecting the application of TCM in the treatment of refractory disease.This efficacy evaluation of TCM syndrome differentiation and treatment of ARDS tries to access to and use of individualized diagnosis and treatment information as a starting point,by extracting differentiation of syndromes of information with Zang and Fu information weighted combination method,combined with the treatment and evaluation of the corresponding information architecture,in order to architecture function mapping model meeting the individual diagnosis and treatment of Chinese medicine characteristics which contains treatment and therapeutic effect of syndrome differentiation.It proposed an analysis method based on weighted mixed regression model for data base matrix for the sake of judging the causal relation between TCM syndrome differentiation and clinical efficacy. |
|
|
|
|
|
