Artificial Intelligence in Medicine
Artificial Intelligence in Medicine
Computational methods for Traditional Chinese Medicine: A survey
Computer Methods and Programs in Biomedicine
Exploration of TCM Masters Knowledge Mining
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007
APPT '09 Proceedings of the 8th International Symposium on Advanced Parallel Processing Technologies
KISTCM: knowledge discovery system for traditional Chinese medicine
Applied Intelligence
Methodological Review: Text mining for traditional Chinese medical knowledge discovery: A survey
Journal of Biomedical Informatics
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We present a novel text mining approach to uncover the functional gene relationships, maybe, temporal and spatial functional modular interaction networks, from MEDLINE in large scale. Other than the regular approaches, which only consider the reductionistic molecular biological knowledge in MEDLINE, we use TCM knowledge(e.g. Symptom Complex) and the 50,000 TCM bibliographic records to automatically congregate the related genes. A simple but efficient bootstrapping technique is used to extract the clinical disease names from TCM literature, and term co-occurrence is used to identify the disease-gene relationships in MEDLINE abstracts and titles. The underlying hypothesis is that the relevant genes of the same Symptom Complex will have some biological interactions. It is also a probing research to study the connection of TCM with modern biomedical and post-genomics studies by text mining. The preliminary results show that Symptom Complex gives a novel top-down view of functional genomics research, and it is a promising research field while connecting TCM with modern life science using text mining.