Abstract
Scientific literature is arguably the most objective, comprehensive and timely data source of medical knowledge discovery and evidence based medicine, as the significant clinical outcomes are often reported in a timely fashion in scientific journals. In this project, we proposed a text mining method for acquiring treatment strategies of intrahepatic bile duct cancer from PubMed abstracts. Treatment related concepts including therapeutic procedures, medications, genes and medical devices were systematically extracted and analyzed. A term co-occurrence network was generated to identify the main topics of the latest research on treatment of intrahepatic bile duct cancer. The treatment relations about 4 groups of different concepts, including Therapeutic Procedure, Medication, Care Activity, and Medical Device, were identified and demonstrated. Our study showed that the automatic treatment strategies extraction from literature with a small amount of physicians' verification added is a feasible solution to quickly characterize the overall treatment research progress.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 43-48 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781538667774 |
| DOIs | |
| State | Published - Jul 16 2018 |
| Externally published | Yes |
| Event | 6th IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018 - New York, United States Duration: Jun 4 2018 → Jun 7 2018 |
Other
| Other | 6th IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018 |
|---|---|
| Country | United States |
| City | New York |
| Period | 6/4/18 → 6/7/18 |
Fingerprint
Keywords
- iCCA
- intrahepatic bile duct cancer
- intrahepatic cholangiocarcinoma
- relation extraction
- text mining
- treatment
ASJC Scopus subject areas
- Information Systems and Management
- Health Informatics
Cite this
Characterizing Treatment Strategies of Intrahepatic Bile Duct Cancer by Literature Mining. / Guo, Hongmei; Zhang, Ning; Hong, Na; Yao, Lixia; Duan, Wenfei; Zhang, Zhixiong.
Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 43-48 8411679.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Characterizing Treatment Strategies of Intrahepatic Bile Duct Cancer by Literature Mining
AU - Guo, Hongmei
AU - Zhang, Ning
AU - Hong, Na
AU - Yao, Lixia
AU - Duan, Wenfei
AU - Zhang, Zhixiong
PY - 2018/7/16
Y1 - 2018/7/16
N2 - Scientific literature is arguably the most objective, comprehensive and timely data source of medical knowledge discovery and evidence based medicine, as the significant clinical outcomes are often reported in a timely fashion in scientific journals. In this project, we proposed a text mining method for acquiring treatment strategies of intrahepatic bile duct cancer from PubMed abstracts. Treatment related concepts including therapeutic procedures, medications, genes and medical devices were systematically extracted and analyzed. A term co-occurrence network was generated to identify the main topics of the latest research on treatment of intrahepatic bile duct cancer. The treatment relations about 4 groups of different concepts, including Therapeutic Procedure, Medication, Care Activity, and Medical Device, were identified and demonstrated. Our study showed that the automatic treatment strategies extraction from literature with a small amount of physicians' verification added is a feasible solution to quickly characterize the overall treatment research progress.
AB - Scientific literature is arguably the most objective, comprehensive and timely data source of medical knowledge discovery and evidence based medicine, as the significant clinical outcomes are often reported in a timely fashion in scientific journals. In this project, we proposed a text mining method for acquiring treatment strategies of intrahepatic bile duct cancer from PubMed abstracts. Treatment related concepts including therapeutic procedures, medications, genes and medical devices were systematically extracted and analyzed. A term co-occurrence network was generated to identify the main topics of the latest research on treatment of intrahepatic bile duct cancer. The treatment relations about 4 groups of different concepts, including Therapeutic Procedure, Medication, Care Activity, and Medical Device, were identified and demonstrated. Our study showed that the automatic treatment strategies extraction from literature with a small amount of physicians' verification added is a feasible solution to quickly characterize the overall treatment research progress.
KW - iCCA
KW - intrahepatic bile duct cancer
KW - intrahepatic cholangiocarcinoma
KW - relation extraction
KW - text mining
KW - treatment
UR - http://www.scopus.com/inward/record.url?scp=85051012650&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85051012650&partnerID=8YFLogxK
U2 - 10.1109/ICHI-W.2018.00013
DO - 10.1109/ICHI-W.2018.00013
M3 - Conference contribution
AN - SCOPUS:85051012650
SP - 43
EP - 48
BT - Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018
PB - Institute of Electrical and Electronics Engineers Inc.
ER -