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An adverse drug effect mentions extraction method based on weighted online recurrent extreme learning machine.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Automatic extraction of adverse drug effect (ADE) mentions from biomedical texts is a challenging research problem that has attracted significant attention from the pharmacovigilance and biomedical text mining communities. I...

Knowledge Domain and Emerging Trends on Echinococcosis Research: A Scientometric Analysis.

International journal of environmental research and public health
The echinococcosis of humans and animals is a chronic helminthic disease caused by the larva of genus tapeworms. It is a globally distributed disease which is an important socioeconomic and public health problem in many low and middle-income countri...

Automatic identification of recent high impact clinical articles in PubMed to support clinical decision making using time-agnostic features.

Journal of biomedical informatics
OBJECTIVES: Finding recent clinical studies that warrant changes in clinical practice ("high impact" clinical studies) in a timely manner is very challenging. We investigated a machine learning approach to find recent studies with high clinical impac...

relSCAN - A system for extracting chemical-induced disease relation from biomedical literature.

Journal of biomedical informatics
This paper proposes an effective and robust approach for Chemical-Induced Disease (CID) relation extraction from PubMed articles. The study was performed on the Chemical Disease Relation (CDR) task of BioCreative V track-3 corpus. The proposed system...

The radiation oncology ontology (ROO): Publishing linked data in radiation oncology using semantic web and ontology techniques.

Medical physics
PURPOSE: Personalized medicine is expected to yield improved health outcomes. Data mining over massive volumes of patients' clinical data is an appealing, low-cost and noninvasive approach toward personalization. Machine learning algorithms could be ...

Biomedical event extraction based on GRU integrating attention mechanism.

BMC bioinformatics
BACKGROUND: Biomedical event extraction is a crucial task in biomedical text mining. As the primary forum for international evaluation of different biomedical event extraction technologies, BioNLP Shared Task represents a trend in biomedical text min...

Fuzzy decision support systems to diagnose musculoskeletal disorders: A systematic literature review.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Musculoskeletal disorders (MSDs) are one of the most important causes of disability with a high prevalence. The accurate and timely diagnosis of these disorders is often difficult. Clinical decision support systems (CDSSs) c...

An effective neural model extracting document level chemical-induced disease relations from biomedical literature.

Journal of biomedical informatics
Since identifying relations between chemicals and diseases (CDR) are important for biomedical research and healthcare, the challenge proposed by BioCreative V requires automatically mining causal relationships between chemicals and diseases which may...

The Role of Artificial Intelligence in Diagnostic Radiology: A Survey at a Single Radiology Residency Training Program.

Journal of the American College of Radiology : JACR
PURPOSE: Advances in artificial intelligence applied to diagnostic radiology are predicted to have a major impact on this medical specialty. With the goal of establishing a baseline upon which to build educational activities on this topic, a survey w...

Drug drug interaction extraction from the literature using a recursive neural network.

PloS one
Detecting drug-drug interactions (DDI) is important because information on DDIs can help prevent adverse effects from drug combinations. Since there are many new DDI-related papers published in the biomedical domain, manually extracting DDI informati...