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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...

Drug Repurposing Prediction for Immune-Mediated Cutaneous Diseases using a Word-Embedding-Based Machine Learning Approach.

The Journal of investigative dermatology
Immune-mediated diseases affect more than 20% of the population, and many autoimmune diseases affect the skin. Drug repurposing (or repositioning) is a cost-effective approach for finding drugs that can be used to treat diseases for which they are cu...

A comparison of word embeddings for the biomedical natural language processing.

Journal of biomedical informatics
BACKGROUND: Word embeddings have been prevalently used in biomedical Natural Language Processing (NLP) applications due to the ability of the vector representations being able to capture useful semantic properties and linguistic relationships between...

Supporting biomedical ontology evolution by identifying outdated concepts and the required type of change.

Journal of biomedical informatics
The consistent evolution of ontologies is a major challenge for systems using semantically enriched data, for example, for annotating, indexing, or reasoning. The biomedical domain is a typical example where ontologies, expressed with different forma...

Automatic extraction of gene-disease associations from literature using joint ensemble learning.

PloS one
A wealth of knowledge concerning relations between genes and its associated diseases is present in biomedical literature. Mining these biological associations from literature can provide immense support to research ranging from drug-targetable pathwa...

OC-2-KB: integrating crowdsourcing into an obesity and cancer knowledge base curation system.

BMC medical informatics and decision making
BACKGROUND: There is strong scientific evidence linking obesity and overweight to the risk of various cancers and to cancer survivorship. Nevertheless, the existing online information about the relationship between obesity and cancer is poorly organi...

Extending PubMed searches to ClinicalTrials.gov through a machine learning approach for systematic reviews.

Journal of clinical epidemiology
OBJECTIVES: Despite their essential role in collecting and organizing published medical literature, indexed search engines are unable to cover all relevant knowledge. Hence, current literature recommends the inclusion of clinical trial registries in ...

A Deep Learning Method to Automatically Identify Reports of Scientifically Rigorous Clinical Research from the Biomedical Literature: Comparative Analytic Study.

Journal of medical Internet research
BACKGROUND: A major barrier to the practice of evidence-based medicine is efficiently finding scientifically sound studies on a given clinical topic.

Deep learning meets ontologies: experiments to anchor the cardiovascular disease ontology in the biomedical literature.

Journal of biomedical semantics
BACKGROUND: Automatic identification of term variants or acceptable alternative free-text terms for gene and protein names from the millions of biomedical publications is a challenging task. Ontologies, such as the Cardiovascular Disease Ontology (CV...

A bibliometric analysis of natural language processing in medical research.

BMC medical informatics and decision making
BACKGROUND: Natural language processing (NLP) has become an increasingly significant role in advancing medicine. Rich research achievements of NLP methods and applications for medical information processing are available. It is of great significance ...