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Natural Language Processing

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Generative Biomedical Event Extraction With Constrained Decoding Strategy.

IEEE/ACM transactions on computational biology and bioinformatics
Currently, biomedical event extraction has received considerable attention in various fields, including natural language processing, bioinformatics, and computational biomedicine. This has led to the emergence of numerous machine learning and deep le...

Relation Extraction in Biomedical Texts: A Cross-Sentence Approach.

IEEE/ACM transactions on computational biology and bioinformatics
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 ...

Integrating K+ Entities Into Coreference Resolution on Biomedical Texts.

IEEE/ACM transactions on computational biology and bioinformatics
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...

Enhancing Generalizability in Biomedical Entity Recognition: Self-Attention PCA-CLS Model.

IEEE/ACM transactions on computational biology and bioinformatics
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...

Utility of a Large Language Model for Extraction of Clinical Findings from Healthcare Data following Lung Ablation: A Feasibility Study.

Journal of vascular and interventional radiology : JVIR
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...

Coherence and comprehensibility: Large language models predict lay understanding of health-related content.

Journal of biomedical informatics
Health literacy is a prerequisite to informed health-related decision making. To facilitate understanding of information, text should be presented at an appropriate reading level for the reader. Cognitive studies suggest that the coherence of a text ...

LCDL: Classification of ICD codes based on disease label co-occurrence dependency and LongFormer with medical knowledge.

Artificial intelligence in medicine
Medical coding involves assigning codes to clinical free-text documents, specifically medical records that average over 3,000 markers, in order to track patient diagnoses and treatments. This is typically accomplished through manual assignments by he...

Self-supervised pre-trained neural network for quantum natural language processing.

Neural networks : the official journal of the International Neural Network Society
Quantum computing models have propelled advances in many application domains. However, in the field of natural language processing (NLP), quantum computing models are limited in representation capacity due to the high linearity of the underlying quan...

Augmenting Large Language Models via Vector Embeddings to Improve Domain-specific Responsiveness.

Journal of visualized experiments : JoVE
Large language models (LLMs) have emerged as a popular resource for generating information relevant to a user query. Such models are created through a resource-intensive training process utilizing an extensive, static corpus of textual data. This sta...