Abstract
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.
Original language | English |
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Title of host publication | Proceedings of 2018 6th International Conference on Bioinformatics and Computational Biology, ICBCB 2018 |
Publisher | Association for Computing Machinery |
Pages | 145-149 |
Number of pages | 5 |
ISBN (Electronic) | 9781450363488 |
DOIs | |
Publication status | Published - Mar 12 2018 |
Event | 6th International Conference on Bioinformatics and Computational Biology, ICBCB 2018 - Chengdu, China Duration: Mar 12 2018 → Mar 14 2018 |
Publication series
Name | ACM International Conference Proceeding Series |
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Other
Other | 6th International Conference on Bioinformatics and Computational Biology, ICBCB 2018 |
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Country | China |
City | Chengdu |
Period | 3/12/18 → 3/14/18 |
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All Science Journal Classification (ASJC) codes
- Human-Computer Interaction
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Software
Cite this
Classification and feature extraction for text-based drug incident report. / Yamashita, Takanori; Nakashima, Naoki; Hirokawa, Sachio.
Proceedings of 2018 6th International Conference on Bioinformatics and Computational Biology, ICBCB 2018. Association for Computing Machinery, 2018. p. 145-149 (ACM International Conference Proceeding Series).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Classification and feature extraction for text-based drug incident report
AU - Yamashita, Takanori
AU - Nakashima, Naoki
AU - Hirokawa, Sachio
PY - 2018/3/12
Y1 - 2018/3/12
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85047157293&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85047157293&partnerID=8YFLogxK
U2 - 10.1145/3194480.3194499
DO - 10.1145/3194480.3194499
M3 - Conference contribution
AN - SCOPUS:85047157293
T3 - ACM International Conference Proceeding Series
SP - 145
EP - 149
BT - Proceedings of 2018 6th International Conference on Bioinformatics and Computational Biology, ICBCB 2018
PB - Association for Computing Machinery
ER -