A novel intelligent model for visualized inference of medical diagnosis: A case of TCM.

How to present an intelligent model based on known diagnostic knowledge to assist medical diagnosis and display the reasoning process is an interesting issue worth exploring. This study developed a novel intelligent model for visualized inference of medical diagnosis with a case of Traditional Chinese Medicine (TCM). Four classes of TCM's diagnosis composed of Yin deficiency, Liver Yin deficiency, Kidney Yin deficiency, and Liver-Kidney Yin deficiency were selected as research examples.

[Bioinformatic analysis of differentially expressed genes and Chinese medicine prediction for ulcerative colitis].

The aim of this paper was to analyze the microarray data between ulcerative colitis(UC) patients and healthy people by bioinformatics technology, screen the differentially expressed genes of UC, and predict the potential Chinese medicines for UC. The GSE36807 gene expression profile was downloaded from the gene expression database(GEO) and the differentially expressed(both up-regulated and down-regulated) genes(DEGs) were analyzed by using R language software. The core genes in the DEGs were obtained by using String database, Cytoscape software and its plug-in analysis, and the gene ontology(GO) and Kyoto encyclopedia of genes and genomes(KEGG) were used to analyze the core genes.

Analysis of molecular networks and targets mining of Chinese herbal medicines on anti-aging.

Background: Many kidney-tonifying Chinese herbal medicines exert effects on anti-aging by comprehensive interactions of multiple targets. However, the interactions of multi-targets targeted by effective ingredients of kidney-tonifying Chinese herbal medicines are unknown. In this study, to explore the systems pharmacology mechanisms of kidney-tonifying Chinese medicines on anti-aging, we establish the molecular networks with the interactions of multi-targets, analyze bio-functions and pathways with IPA, and calculated the mutual interaction pairs of targets (target pairs) with data mining, respectively.