Year: 2022
Type: article
Abstract: Although advanced text mining methods specifically adapted to the biomedical domain are continuously being developed, their applications on large scale have been scarce.One of the main reasons for this is the lack of computational resources and workforce required for processing large text corpora.In this paper we present a publicly available resource distributing preprocessed biomedical literature including sentence splitting, tokenization, part-of-speech tagging, syntactic parses and named entity recognition.The aim of this work is to support the future development of largescale text mining resources by eliminating the time consuming but necessary preprocessing steps.This resource covers the whole of PubMed and
Source: UTUPub (University of Turku)
Authors: Kai Hakala, Suwisa Kaewphan, Tapio Salakoski, Filip Ginter
Institutions: University of Turku, Turku Centre for Computer Science
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funder: China Scholarship Council
OpenAlex ID: W7081592488