OBJECTIVE:  Distinguishing between medically indicated induction of labor (iIOL) and elective induction of labor (eIOL) is a daunting process for researchers. We aimed to develop a Natural Language Processing (NLP) algorithm to identify eIOLs from el...
Document-level interaction extraction for Chemical-Disease is aimed at inferring the interaction relations between chemical entities and disease entities across multiple sentences. Compared with sentence-level relation extraction, document-level rela...
BMC medical informatics and decision making
Aug 29, 2024
BACKGROUND: Medical text, as part of an electronic health record, is an essential information source in healthcare. Although natural language processing (NLP) techniques for medical text are developing fast, successful transfer into clinical practice...
Aphasia is a language disorder caused by brain injury that often results in difficulties with speech production and comprehension, significantly impacting the affected individuals' lives. Recently, artificial intelligence (AI) has been advancing in m...
The task of question matching/retrieval focuses on determining whether two questions are semantically equivalent. It has garnered significant attention in the field of natural language processing (NLP) due to its commercial value. While neural networ...
BACKGROUND AND OBJECTIVE: Biomedical relation extraction aims to reveal the relation between entities in medical texts. Currently, the relation extraction models that have attracted much attention are mainly to fine-tune the pre-trained language mode...
Radiology report generation automates diagnostic narrative synthesis from medical imaging data. Current report generation methods primarily employ knowledge graphs for image enhancement, neglecting the interpretability and guiding function of the kno...
Hundreds of millions of people now interact with language models, with uses ranging from help with writing to informing hiring decisions. However, these language models are known to perpetuate systematic racial prejudices, making their judgements bia...
Medical Concept Normalization (MCN) is a crucial process for deep information extraction and natural language processing tasks, which plays a vital role in biomedical research. Although MCN in English has achieved significant research achievements, C...
Drug-induced liver injury (DILI) stands as a significant concern in drug safety, representing the primary cause of acute liver failure. Identifying the scientific literature related to DILI is crucial for monitoring, investigating, and conducting met...