OBJECTIVE: Motivated by the well documented worldwide spread of adverse drug events, as well as the increased danger of antibiotic resistance (caused mainly by inappropriate prescribing and overuse), we propose a novel recommendation system for antib...
Computer methods and programs in biomedicine
Oct 4, 2019
BACKGROUND AND OBJECTIVE: Capturing the context of text is a challenging task in biomedical text summarization. The objective of this research is to show how contextualized embeddings produced by a deep bidirectional language model can be utilized to...
Drug-drug interactions are critical in studying drug side effects. Thus, quickly and accurately identifying the relationship between drugs is necessary. Current methods for biomedical relation extraction include only the sequential information of sen...
The explosive growth of biomedical literature has created a rich source of knowledge, such as that on protein-protein interactions (PPIs) and drug-drug interactions (DDIs), locked in unstructured free text. Biomedical relation classification aims to ...
Clinical named entity recognition (CNER), which intends to automatically detect clinical entities in electronic health record (EHR), is a committed step for further clinical text mining. Recently, more and more deep learning models are used to Chines...
Named entity recognition is a fundamental and crucial task in medical natural language processing problems. In medical fields, Chinese clinical named entity recognition identifies boundaries and types of medical entities from unstructured text such a...
BACKGROUND: In the last ten years, the international workshop on knowledge representation for health care (KR4HC) has hosted outstanding contributions of the artificial intelligence in medicine community pertaining to the formalization and representa...
The identification of medical concepts, their attributes and the relations between concepts in a large corpus of Electroencephalography (EEG) reports is a crucial step in the development of an EEG-specific patient cohort retrieval system. However, th...
OBJECTIVE: The aim of this study is to analyze and visualize blood pressure (BP) patterns during continuous hemodialysis (HD) sessions, referred to as multiple-session patterns (MSPs), and explore whether deep learning models with MSPs have better pe...
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