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Information retrieval and text mining technologies for chemistry
Efficient access to chemical information contained in scientific literature, patents, technical
reports, or the web is a pressing need shared by researchers and patent attorneys from …
reports, or the web is a pressing need shared by researchers and patent attorneys from …
A survey on extraction of causal relations from natural language text
As an essential component of human cognition, cause–effect relations appear frequently in
text, and curating cause–effect relations from text helps in building causal networks for …
text, and curating cause–effect relations from text helps in building causal networks for …
A neural joint model for entity and relation extraction from biomedical text
Background Extracting biomedical entities and their relations from text has important
applications on biomedical research. Previous work primarily utilized feature-based pipeline …
applications on biomedical research. Previous work primarily utilized feature-based pipeline …
Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task
Manually curating chemicals, diseases and their relationships is significantly important to
biomedical research, but it is plagued by its high cost and the rapid growth of the biomedical …
biomedical research, but it is plagued by its high cost and the rapid growth of the biomedical …
Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research
Background Current biomedical research needs to leverage and exploit the large amount of
information reported in scientific publications. Automated text mining approaches, in …
information reported in scientific publications. Automated text mining approaches, in …
Adverse drug events and medication relation extraction in electronic health records with ensemble deep learning methods
Objective Identification of drugs, associated medication entities, and interactions among
them are crucial to prevent unwanted effects of drug therapy, known as adverse drug events …
them are crucial to prevent unwanted effects of drug therapy, known as adverse drug events …
[HTML][HTML] Causal relationship extraction from biomedical text using deep neural models: A comprehensive survey
The identification of causal relationships between events or entities within biomedical texts
is of great importance for creating scientific knowledge bases and is also a fundamental …
is of great importance for creating scientific knowledge bases and is also a fundamental …
Adverse drug event detection in tweets with semi-supervised convolutional neural networks
Current Adverse Drug Events (ADE) surveillance systems are often associated with a
sizable time lag before such events are published. Online social media such as Twitter could …
sizable time lag before such events are published. Online social media such as Twitter could …
[HTML][HTML] PKDE4J: Entity and relation extraction for public knowledge discovery
Due to an enormous number of scientific publications that cannot be handled manually,
there is a rising interest in text-mining techniques for automated information extraction …
there is a rising interest in text-mining techniques for automated information extraction …
[HTML][HTML] Clinical relation extraction toward drug safety surveillance using electronic health record narratives: classical learning versus deep learning
Background: Medication and adverse drug event (ADE) information extracted from electronic
health record (EHR) notes can be a rich resource for drug safety surveillance. Existing …
health record (EHR) notes can be a rich resource for drug safety surveillance. Existing …