| Literature DB >> 32308886 |
Liwei Wang1, Jason Wampfler1, Angela Dispenzieri1, Hua Xu2, Ping Yang3, Hongfang Liu1.
Abstract
Accurate identification of temporal information such as date is crucial for advancing cancer research which often requires precise date information associated with related cancer events. However, there is a gap for existing natural language processing (NLP) systems to identify dates for specific cancer research studies. Illustrated with two case studies, we investigated the feasibility, evaluated the performances and discussed the challenges of date information extraction for cancer research. ©2019 AMIA - All rights reserved.Entities:
Year: 2020 PMID: 32308886 PMCID: PMC7153063
Source DB: PubMed Journal: AMIA Annu Symp Proc ISSN: 1559-4076