Results 21 to 30 of about 157,658 (286)
OntoGene web services for biomedical text mining. [PDF]
BMC Bioinformatics, 2014 Text mining services are rapidly becoming a crucial component of various knowledge management pipelines, for example in the process of database curation, or for exploration and enrichment of biomedical data within the pharmaceutical industry. Traditional architectures, based on monolithic applications, do not offer sufficient flexibility for a wide ...
Rinaldi F +5 more
europepmc +4 more sources
BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining [PDF]
Briefings Bioinform., 2022 Pre-trained language models have attracted increasing attention in the biomedical domain, inspired by their great success in the general natural language domain. Among the two main branches of pre-trained language models in the general language domain, i.
Renqian Luo +6 more
semanticscholar +1 more source
RuBioRoBERTa: a pre-trained biomedical language model for Russian language biomedical text mining [PDF]
arXiv.org, 2022 This paper presents several BERT-based models for Russian language biomedical text mining (RuBioBERT, RuBioRoBERTa). The models are pre-trained on a corpus of freely available texts in the Russian biomedical domain.
Alexander Yalunin +2 more
semanticscholar +1 more source
Organizing an in-class hackathon to correct PDF-to-text conversion errors of 1.0 [PDF]
Genomics & Informatics, 2020 This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first ...
Sunho Kim +44 more
doaj +1 more source
BMC Bioinformatics, 2022 Background Recently, automatically extracting biomedical relations has been a significant subject in biomedical research due to the rapid growth of biomedical literature.
Peng Su, K. Vijay-Shanker
doaj +1 more source
Web Interface of NER and RE with BERT for Biomedical Text Mining
Applied Sciences, 2023 The BioBERT Named Entity Recognition (NER) model is a high-performance model designed to identify both known and unknown entities. It surpasses previous NER models utilized by text-mining tools, such as tmTool and ezTag, in effectively discovering novel ...
Ye In Park +4 more
semanticscholar +1 more source
An extensive benchmark study on biomedical text generation and mining with ChatGPT
Bioinform., 2023 Motivation In recent years, the development of natural language process (NLP) technologies and deep learning hardware has led to significant improvement in large language models (LLMs).
Qijie Chen +9 more
semanticscholar +1 more source
Healthcare, 2023 Biomedical-named entity recognition (bNER) is critical in biomedical informatics. It identifies biomedical entities with special meanings, such as people, places, and organizations, as predefined semantic types in electronic health records (EHR). bNER is
Pir Noman Ahmad +2 more
semanticscholar +1 more source
An Empirical Study of Multi-Task Learning on BERT for Biomedical Text Mining [PDF]
Workshop on Biomedical Natural Language Processing, 2020 Multi-task learning (MTL) has achieved remarkable success in natural language processing applications. In this work, we study a multi-task learning model with multiple decoders on varieties of biomedical and clinical natural language processing tasks ...
Yifan Peng, Qingyu Chen, Zhiyong Lu
semanticscholar +1 more source
Opinion: Strategy of Semi-Automatically Annotating a Full-Text Corpus of [PDF]
Genomics & Informatics, 2018 There is a communal need for an annotated corpus consisting of the full texts of biomedical journal articles. In response to community needs, a prototype version of the full-text corpus of Genomics & Informatics, called GNI version 1.0, has recently been
Hyun-Seok Park
doaj +1 more source