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Towards a characterization of apparent contradictions in the biomedical literature using context analysis.

Journal of biomedical informatics
BACKGROUND: With the substantial growth in the biomedical research literature, a larger number of claims are published daily, some of which seemingly disagree with or contradict prior claims on the same topics. Resolving such contradictions is critic...

Trends in Alzheimer's Disease Research Based upon Machine Learning Analysis of PubMed Abstracts.

International journal of biological sciences
About 29.8 million people worldwide had been diagnosed with Alzheimer's disease (AD) in 2015, and the number is projected to triple by 2050. In 2018, AD was the fifth leading cause of death in Americans with 65 years of age or older, but the progress...

Distant supervision for treatment relation extraction by leveraging MeSH subheadings.

Artificial intelligence in medicine
The growing body of knowledge in biomedicine is too vast for human consumption. Hence there is a need for automated systems able to navigate and distill the emerging wealth of information. One fundamental task to that end is relation extraction, wher...

Extracting chemical-protein interactions from biomedical literature via granular attention based recurrent neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The extraction of interactions between chemicals and proteins from biomedical literature is important for many biomedical tasks such as drug discovery and precision medicine. In the existing systems, the methods achieving co...

Gene fingerprint model for literature based detection of the associations among complex diseases: a case study of COPD.

BMC medical informatics and decision making
BACKGROUND: Disease comorbidity is very common and has significant impact on disease treatment. Revealing the associations among diseases may help to understand the mechanisms of diseases, improve the prevention and treatment of diseases, and support...

A neural classification method for supporting the creation of BioVerbNet.

Journal of biomedical semantics
BACKGROUND: VerbNet, an extensive computational verb lexicon for English, has proved useful for supporting a wide range of Natural Language Processing tasks requiring information about the behaviour and meaning of verbs. Biomedical text processing an...

Fast and scalable neural embedding models for biomedical sentence classification.

BMC bioinformatics
BACKGROUND: Biomedical literature is expanding rapidly, and tools that help locate information of interest are needed. To this end, a multitude of different approaches for classifying sentences in biomedical publications according to their coarse sem...

A comparative quantitative study of utilizing artificial intelligence on electronic health records in the USA and China during 2008-2017.

BMC medical informatics and decision making
BACKGROUND: The application of artificial intelligence techniques for processing electronic health records data plays increasingly significant role in advancing clinical decision support. This study conducts a quantitative comparison on the research ...

Mining Disease-Symptom Relation from Massive Biomedical Literature and Its Application in Severe Disease Diagnosis.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Disease-symptom relation is an important biomedical relation that can be used for clinical decision support including building medical diagnostic systems. Here we present a study on mining disease-symptom relation from massive biomedical literature a...

Finding medication doses in the liteature.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Medication doses, one of the determining factors in medication safety and effectiveness, are present in the literature, but only in free-text form. We set out to determine if the systems developed for extracting drug prescription information from cli...