Expression model for multiple relationships in the ontology of traditional Chinese medicine knowledge

AbstractObjectiveTo explore multiple relationships in traditional Chinese medicine (TCM) knowledge by comparing binary and multiple relationships during knowledge organization.MethodsCharacteristics of binary and multiple semantic relationships as well as their associations are described. A method to classify multiple relationships based on the involvement of time is proposed and theoretically validated using examples from the ancient TCM classic Important Formulas Worth a Thousand Gold Pieces. The classification includes parallel multiple relationships, restricted multiple relationships, multiple relationships that involve time, and multiple relationships that involve time restriction. Next, construction of multiple semantic relationships for TCM concepts in each classification using Protégé, an ontology editing tool is described.ResultsProtégé is superior to a binary relationship and less than ideal with multiple relationships during the constitution of concept relationships.ConclusionWhen applied in TCM, the semantic relationships constructed by Protégé are superior than those constructed by correlation and/or attribute relationships, but less ideal than those constructed by the human cognitive process

In Silico Syndrome Prediction for Coronary Artery Disease in Traditional Chinese Medicine

Coronary artery disease (CAD) is the leading causes of deaths in the world. The differentiation of syndrome (ZHENG) is the criterion of diagnosis and therapeutic in TCM. Therefore, syndrome prediction in silico can be improving the performance of treatment. In this paper, we present a Bayesian network framework to construct a high-confidence syndrome predictor based on the optimum subset, that is, collected by Support Vector Machine (SVM) feature selection. Syndrome of CAD can be divided into asthenia and sthenia syndromes. According to the hierarchical characteristics of syndrome, we firstly label every case three types of syndrome (asthenia, sthenia, or both) to solve several syndromes with some patients. On basis of the three syndromes' classes, we design SVM feature selection to achieve the optimum symptom subset and compare this subset with Markov blanket feature select using ROC. Using this subset, the six predictors of CAD's syndrome are constructed by the Bayesian network technique. We also design Naïve Bayes, C4.5 Logistic, Radial basis function (RBF) network compared with Bayesian network. In a conclusion, the Bayesian network method based on the optimum symptoms shows a practical method to predict six syndromes of CAD in TCM

Progresses and challenges in the traditional medicine information system: A systematic review

Context: Traditional medicine information system (TMIS) is a substructure founded on the targeted application of technology. It also serves as a tool supporting the decisions in traditional medicine (TM). However, due to following a different approach in the treatment process, the TM has faced some challenges. Aims: To review the universal progresses and challenges in TMIS. Methods: This study was conducted using systematic search and review. The resources were retrieved through searching the key words related to the TMIS in the available databases including Science Direct, WOS, ProQuest, PubMed and IEEE. The findings were classified in to two distinct categories of progresses and challenges relating to the TMIS. Results: As many as 28 studies conducted from 2000 to 2017 were included in this research. The majority of the studies were related to 2010 or after 2010 conducted in China. Progresses identified in this TMIS were categorized into four types including the development of the database, universal standardization of the TM, development of the clinical data warehouse, and application of information technology in the TM. The challenges were classified into four distinct categories, namely the lack of treatment protocols in TM, the necessity of developing a universal unified terminology, the necessity of creating a medical ontologies and the necessity of ensuring the data quality. Conclusions: Information technology forms a significant aspect of the TM modernization. To develop both the TMIS and the knowledge sharing tools, it is necessary to remove the problems and challenges involved in the data record process in the TM. Keywords Author Keywords:challenges; herbal medicine; information systems; opportunity; traditional medicine KeyWords Plus:WESTERN HERBAL MEDICINE; CHINESE MEDICINE; KNOWLEDGE; MECHANISM; PRODUCTS; DATABASE; STAT

Internet Predictions

More than a dozen leading experts give their opinions on where the Internet is headed and where it will be in the next decade in terms of technology, policy, and applications. They cover topics ranging from the Internet of Things to climate change to the digital storage of the future. A summary of the articles is available in the Web extras section

An ontology-based approach for data integration in regionally interoperable healthcare systems

In order to best utilize the limited resource of medical resources, and to reduce the cost and improve the quality of medical treatment, we propose to build an interoperable regional healthcare systems among several levels of medical treatment organizations. In this paper, our approaches are as follows:(1) the ontology based approach is introduced as the methodology and technological solution for information integration; (2) the integration framework of data sharing among different organizations are proposed(3)the virtual database to realize data integration of hospital information system is established. Our methods realize the effective management and integration of the medical workflow and the mass information in the interoperable regional healthcare system. Furthermore, this research provides the interoperable regional healthcare system with characteristic of modularization, expansibility and the stability of the system is enhanced by hierarchy structure