Classification and Feature Extraction for Text-based Drug Incident Report
Medical institutions have been constructed incident report system,then accumulating incident data.Incident data compose text-based data and some structured attributes.We considered based on the analysis result with clustering for drug incident report.Firstly, we generated a network of documents and words from the text-based data.Secondly, Louvain method was applied to the network and 11 clusters were generated.We confirmed the contents of each cluster from feature words extracted by TF-IDF.Then, we compare clusters of text-based data with structured attributes and grasp the trend of the incident.This proposed method showed the possibility of clinical support toward reduction incident from text-based data.
Text mining Louvain method Incident report
Takanori Yamashita Naoki Nakashima Sachio Hirokawa
Medical Information Center, Kyushu University Hospital 3-1-1 Maidashi, Higashi-ku Fukuoka, Japan Research Institute for Information Technology, Kyushu University 374 Motooka, Nishi-ku Fukuoka, Japa
国际会议
成都
英文
145-149
2018-03-12（万方平台首次上网日期，不代表论文的发表时间）