@inproceedings{82dff66ced554f41a15ec97bd220aff3,
title = "MedC: Exploring and predicting medicine interactions to support integrative chinese medicine",
abstract = "Chinese medicine is increasingly being used with Western medicine in practice, especially for treatment of chronic diseases. In this integrative medicine process, it is necessary to understand the interactions between Chinese and Western medicine to reduce adverse events. However, compared to Western medicine, there are limited studies that summarize findings on Chinese medicine interactions and effectively present such findings to practitioners. Built upon the MedC literature analysis system, this paper proposes a Chinese medicine analysis and prediction framework that can effectively present Chinese medicine interactions and connect them with the clinical evidence documented in literature. The system can support Chinese medicine scholars and facilitate research on integrative Chinese medicine.",
keywords = "Chinese medicine, Drug interaction, Text mining, Visualization",
author = "Xin Li and Haobo Gu and Yu Tong",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; International Conference for Smart Health, ICSH 2016 ; Conference date: 24-12-2016 Through 25-12-2016",
year = "2017",
doi = "10.1007/978-3-319-59858-1\_15",
language = "English",
isbn = "9783319598574",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "155--165",
editor = "Ye Liang and Chunxiao Xing and Yong Zhang",
booktitle = "Smart Health - International Conference, ICSH 2016, Revised Selected Papers",
address = "Germany",
}