RT Journal Article
SR Electronic
T1 deepMINE - Natural Language Processing based Automatic Literature Mining and Research Summarization for Early-Stage Comprehension in Pandemic Situations specifically for COVID-19
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.03.30.014555
DO 10.1101/2020.03.30.014555
A1 Bhrugesh Joshi
A1 Vishvajit Bakarola
A1 Parth Shah
A1 Ramar Krishnamurthy
YR 2020
UL http://biorxiv.org/content/early/2020/04/02/2020.03.30.014555.abstract
AB The recent pandemic created due to Novel Coronavirus (nCOV-2019) from Wuhan, China demanding a large scale of a general health emergency. This demands novel research on the vaccine to fight against this pandemic situation, re-purposing of the existing drugs, phylogenetic analysis to identify the origin and determine the similarity with other known viruses, etc. The very preliminary task from the research community is to analyze the wide verities of existing related research articles, which is very much time-consuming in such situations where each minute counts for saving hundreds of human lives. The entire manual processing is even lower down the efficiency in mining the information. We have developed a complete automatic literature mining system that delivers efficient and fast mining from existing biomedical literature databases. With the help of modern-day deep learning algorithms, our system also delivers a summarization of important research articles that provides ease and fast comprehension of critical research articles. The system is currently scanning nearly 1,46,115,136 English words from 29,315 research articles in not greater than 1.5 seconds with multiple search keywords. Our research article presents the criticality of literature mining, especially in pandemic situations with the implementation and online deployment of the system.