Comparative study of pulse-diagnosis signals between 2 kinds of liver disease patients based on the combination of unsupervised learning and supervised learning

Objective: To compare the signals of pulse-diagnosis of 2 kinds of liver disease patients: Fatty Liver Disease (FLD) and Cirrhosis. Methods: After collecting the pulse waves of patients with Fatty Liver, Cirrhosis, we do pretreatment, parameter extracting basing on harmonic fitting, modeling, and identification by unsupervised learning and supervised learning with cross-validation step by step for analysis. Results: There is significant difference between the pulse-diagnosis signals of patients with FLD and Cirrhosis, and the result was confirmed by 3 analysis methods. The identification accurate is 72%–91%. Conclusion: Pulse waves collected from radial artery basing on the theory of TCM are specific for different pathological conditions. And the analysis methods we built in this study might offer some confidence for the realization of computer-aided diagnosis by pulse-diagnosis in TCM.