IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
Relation extraction, a crucial task in understanding the intricate relationships between entities in biomedical domains, has predominantly focused on binary relations within single sentences. However, in practical biomedical scenarios, relationships ...
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
Hypothesis Generation (HG) aims to expedite biomedical researches by generating novel hypotheses from existing scientific literature. Most existing studies focused on modeling static snapshots of the corpus, neglecting the temporal evolution of scien...
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
Biomedical Coreference Resolution focuses on identifying the coreferences in biomedical texts, which normally consists of two parts: (i) mention detection to identify textual representation of biological entities and (ii) finding their coreference li...
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
Biomedical event detection is a pivotal information extraction task in molecular biology and biomedical research, which provides inspiration for the medical search, disease prevention, and new drug development. The existing methods usually detect sim...
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
One of the primary tasks in the early stages of data mining involves the identification of entities from biomedical corpora. Traditional approaches relying on robust feature engineering face challenges when learning from available (un-)annotated data...
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
Biomedical relation extraction aims to identify underlying relationships among entities, such as gene associations and drug interactions, within biomedical texts. Despite advancements in relation extraction in general knowledge domains, the scarcity ...
Journal of vascular and interventional radiology : JVIR
Dec 9, 2024
To assess the feasibility of utilizing a large language model (LLM) in extracting clinically relevant information from healthcare data in patients who have undergone microwave ablation for lung tumors. In this single-center retrospective study, radio...
BACKGROUND: Suicide is a leading cause of death worldwide, making early identification of suicidal behaviors crucial for clinicians. Current Natural Language Processing (NLP) approaches for identifying suicidal behaviors in Electronic Health Records ...
In this study, we revisit named entity recognition (NER) in the biomedical domain from a multimodal perspective, with a particular focus on applications in low-resource languages. Existing research primarily relies on unimodal methods for NER, which ...
In contrast to sentence-level relational extraction, document-level relation extraction poses greater challenges as a document typically contains multiple entities, and one entity may be associated with multiple other entities. Existing methods often...
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