ISMAC: An Intelligent System for Customized Clinical Case Management and Analysis.
Clinical cases are primary and vital evidence for Traditional Chinese Medicine (TCM) clinical research. A great deal of medical knowledge is hidden in the clinical cases of the highly experienced TCM practitioner. With a deep Chinese culture background and years of clinical experience, an experienced TCM specialist usually has his or her unique clinical pattern and diagnosis idea. Preserving huge clinical cases of experienced TCM practitioners as well as exploring the inherent knowledge is then an important but arduous task. The novel system ISMAC (Intelligent System for Management and Analysis of Clinical Cases in TCM) is designed and implemented for customized management and intelligent analysis of TCM clinical data. Customized templates with standard and expert-standard symptoms, diseases, syndromes, and Chinese Medince Formula (CMF) are constructed in ISMAC, according to the clinical diagnosis and treatment characteristic of each TCM specialist. With these templates, clinical cases are archived in order to maintain their original characteristics. Varying data analysis and mining methods, grouped as Basic Analysis, Association Rule, Feature Reduction, Cluster, Pattern Classification, and Pattern Prediction, are implemented in the system. With a flexible dataset retrieval mechanism, ISMAC is a powerful and convenient system for clinical case analysis and clinical knowledge discovery.
Department of Control Science and Engineering, Tongji University, Shanghai 200000, China.
Mingyu
M
You
Department of Control Science and Engineering, Tongji University, Shanghai 200000, China.
Chong
C
Chen
Department of Control Science and Engineering, Tongji University, Shanghai 200000, China.
Guo-Zheng
GZ
Li
Department of Control Science and Engineering, Tongji University, Shanghai 200000, China.
Shi-Xing
SX
Yan
Department of Control Science and Engineering, Tongji University, Shanghai 200000, China.
Sheng
S
Sun
Computer Center, Nanchang University, Nanchang 330000, China.
Xue-Qiang
XQ
Zeng
Department of Control Science and Engineering, Tongji University, Shanghai 200000, China.
Qing-Ce
QC
Zhao
Shanghai Institute of Traditional Chinese Medical Literatures, Shanghai 200000, China.
Liao-Yu
LY
Xu
Shanghai Institute of Traditional Chinese Medical Literatures, Shanghai 200000, China.
Su-Ying
SY
Huang
D019090:Case Management; D003625:Data Collection; D006801:Humans; D013223:Statistics as Topic; D013577:Syndrome