Author:
Xu Quan,Liu Yueyue,Sun Dawei,Hu Jifang,Duan Xiaohong,Song Niuben,Zhou Jiale,Su Junyan,Liu Siyao,Chen Fan,Guo Zhongjia,Li Hexiang,Zhou Qiming,Niu Beifang
Abstract
ABSTRACTKnowledge bases that are up-to-date and of expert quality are fundamental in biomedical research fields. A knowledge base established with human participation and subjected to multiple inspections is crucial for supporting clinical decision-making, especially in the exponentially growing field of precision oncology. The number of original publications in the field has skyrocketed with the advancement of technology and in-depth research evolved. It has become an increasingly pressing issue that researchers need to consider how to gather and mine these articles accurately and efficiently. In this paper, we present OncoPubMiner (https://oncopubminer.chosenmedinfo.com), a free and powerful system that combines text mining, data structure customization, publication search with online reading, project-centered and team-based data collection to realize a one-stop “keyword in, knowledge out” oncology publication mining platform. It was built by integrating all the open-access abstracts from PubMed and full-text articles from PubMed Central, and is updated on a daily basis. The system makes it straightforward to obtain precision oncology knowledge from scientific articles. OncoPubMiner will assist researchers in developing professional structured knowledge base systems efficiently, and bringing the oncology community closer to achieving precision oncology goals.Graphical AbstractOncoPubMiner’s one-stop “keyword in, knowledge out” workflow (A) is built on key features such as text mining (B), publication search (C), form customization (D), and team-based curation (E).
Publisher
Cold Spring Harbor Laboratory
Cited by
1 articles.
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