Text mining approaches for dealing with the rapidly expanding literature on COVID-19
More than 50 000 papers have been published about COVID-19 since the beginning of
2020 and several hundred new papers continue to be published every day. This incredible …
2020 and several hundred new papers continue to be published every day. This incredible …
Unsupervised and self-supervised deep learning approaches for biomedical text mining
M Nadif, F Role - Briefings in Bioinformatics, 2021 - academic.oup.com
Biomedical scientific literature is growing at a very rapid pace, which makes increasingly
difficult for human experts to spot the most relevant results hidden in the papers …
difficult for human experts to spot the most relevant results hidden in the papers …
Self-alignment pretraining for biomedical entity representations
Despite the widespread success of self-supervised learning via masked language models
(MLM), accurately capturing fine-grained semantic relationships in the biomedical domain …
(MLM), accurately capturing fine-grained semantic relationships in the biomedical domain …
BERN2: an advanced neural biomedical named entity recognition and normalization tool
In biomedical natural language processing, named entity recognition (NER) and named
entity normalization (NEN) are key tasks that enable the automatic extraction of biomedical …
entity normalization (NEN) are key tasks that enable the automatic extraction of biomedical …
[HTML][HTML] Building a PubMed knowledge graph
PubMed® is an essential resource for the medical domain, but useful concepts are either
difficult to extract or are ambiguous, which has significantly hindered knowledge discovery …
difficult to extract or are ambiguous, which has significantly hindered knowledge discovery …
[HTML][HTML] Enhancing phenotype recognition in clinical notes using large language models: PhenoBCBERT and PhenoGPT
To enhance phenotype recognition in clinical notes of genetic diseases, we developed two
models—PhenoBCBERT and PhenoGPT—for expanding the vocabularies of Human …
models—PhenoBCBERT and PhenoGPT—for expanding the vocabularies of Human …
Pre-trained language model for biomedical question answering
The recent success of question answering systems is largely attributed to pre-trained
language models. However, as language models are mostly pre-trained on general domain …
language models. However, as language models are mostly pre-trained on general domain …
ChimerDB 4.0: an updated and expanded database of fusion genes
Fusion genes represent an important class of biomarkers and therapeutic targets in cancer.
ChimerDB is a comprehensive database of fusion genes encompassing analysis of deep …
ChimerDB is a comprehensive database of fusion genes encompassing analysis of deep …
[HTML][HTML] A pre-training and self-training approach for biomedical named entity recognition
S Gao, O Kotevska, A Sorokine, JB Christian - PloS one, 2021 - journals.plos.org
Named entity recognition (NER) is a key component of many scientific literature mining
tasks, such as information retrieval, information extraction, and question answering; …
tasks, such as information retrieval, information extraction, and question answering; …
Exploring new digital therapeutics technologies for psychiatric disorders using BERTopic and PatentSBERTa
Abstract Coronavirus disease 2019 (COVID-19) has accelerated the growth of the digital
therapeutics (DTx) market; therefore, development strategies for new DTx products are …
therapeutics (DTx) market; therefore, development strategies for new DTx products are …