K4ThaiHealth: A prototype for Thai routine medical research knowledge extraction sharing

• Main Authors: Jarernsri Mitrpanont, Wudhichart Sawangphol, Thanita Vithantirawat, Sinattaya Paengkaew, Prameyuda Suwannasing
• Other Authors: Mahidol University
• Format: Conference or Workshop Item
• Published: 2019
• Subjects: Computer Science
• Online Access: https://repository.li.mahidol.ac.th/handle/123456789/45552

© 2018 IEEE. 'Routine to Research' (R2R) is well known for Thai research related to the development of routine works of medical and public health practitioners. R2R research contains useful practical knowledge beneficial to the health of Thai people. However, this knowledge cannot be shared easily because it is unstructured and not classified text, moreover, no tool for R2R Thai knowledge sharing yet. In this research, we attempt to use text mining techniques to get insights of R2R research data and the K4ThaiHealth is first implemented as a prototype for basic R2R knowledge sharing. A set of basic medical corpus are developed using Thai medical International Statistical Classification of Diseases and Related Health Problems (ICD10TM) and several resources. They are used for R2R Thai medical text classification and key terms relationship extraction. The results are classified into diseases, organs, symptoms, and others. K4ThaiHealth is then used as a knowledge sharing prototype to offer health and medical practice knowledge extracted from R2R data sharing to Thai people. R2R WordCloud and R2R WordNet are used to display the diseases knowledge extracted from R2R research data and their relationships to diseases, organs, symptoms and others are visualized.