Study of Traditional Chinese Medical Diagnostic Platform Establishment for Hyperlipemia

AbstractHyperlipemia syndrome diagnosis standardizing research is the hotspot in Chinese medicine domain. A traditional Chinese medical diagnostic platform for hyperlipemia is established, which is consisted of four information collection modules including tongue images acquisition, facial image acquisition, inquiry diagnosis, pulse diagnosis, and auscultation diagnosis information. Through this platform, 316 cases of hyperlipemia clinical information have been gathered. A clustering algorithm is applied to analyze hyperlipemia clinical symptoms data based on these samples to get statistically significant classification results, and find the corresponding relationship between these results and syndromes. Clustering algorithm is programmed to classify syndromes and setting similarity threshold interface is available, which make it is possible to classify a large number of samples more adaptively. Compare disease characteristics of samples in every category with syndromes category and find out the relationships between them, by which the foundation of hyperlipemia syndrome differentiation standardization will be establish. Samples are classified to five categories. Finally, an threshold similarity detection algorithm is used to classify a new sample collected by the system to one of the five categories, which can give a syndrome classification suggestion based on statistics to Chinese medical doctors, which will improve the diagnostic efficiency and diagnostic accuracy