AIMC Topic: Natural Language Processing

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Toward a complete dataset of drug-drug interaction information from publicly available sources.

Journal of biomedical informatics
Although potential drug-drug interactions (PDDIs) are a significant source of preventable drug-related harm, there is currently no single complete source of PDDI information. In the current study, all publically available sources of PDDI information ...

Development of phenotype algorithms using electronic medical records and incorporating natural language processing.

BMJ (Clinical research ed.)
Electronic medical records are emerging as a major source of data for clinical and translational research studies, although phenotypes of interest need to be accurately defined first. This article provides an overview of how to develop a phenotype al...

A Fuzzy Computing Model for Identifying Polarity of Chinese Sentiment Words.

Computational intelligence and neuroscience
With the spurt of online user-generated contents on web, sentiment analysis has become a very active research issue in data mining and natural language processing. As the most important indicator of sentiment, sentiment words which convey positive an...

Evaluating a pivot-based approach for bilingual lexicon extraction.

Computational intelligence and neuroscience
A pivot-based approach for bilingual lexicon extraction is based on the similarity of context vectors represented by words in a pivot language like English. In this paper, in order to show validity and usability of the pivot-based approach, we evalua...

Self-training in significance space of support vectors for imbalanced biomedical event data.

BMC bioinformatics
BACKGROUND: Pairwise relationships extracted from biomedical literature are insufficient in formulating biomolecular interactions. Extraction of complex relations (namely, biomedical events) has become the main focus of the text-mining community. How...

Natural language processing as an alternative to manual reporting of colonoscopy quality metrics.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The adenoma detection rate (ADR) is a quality metric tied to interval colon cancer occurrence. However, manual extraction of data to calculate and track the ADR in clinical practice is labor-intensive. To overcome this difficulty...

Automatic evidence quality prediction to support evidence-based decision making.

Artificial intelligence in medicine
BACKGROUND: Evidence-based medicine practice requires practitioners to obtain the best available medical evidence, and appraise the quality of the evidence when making clinical decisions. Primarily due to the plethora of electronically available data...

Automated methods for the summarization of electronic health records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: This review examines work on automated summarization of electronic health record (EHR) data and in particular, individual patient record summarization. We organize the published research and highlight methodological challenges in the area...

DyKOSMap: A framework for mapping adaptation between biomedical knowledge organization systems.

Journal of biomedical informatics
BACKGROUND: Knowledge Organization Systems (KOS) and their associated mappings play a central role in several decision support systems. However, by virtue of knowledge evolution, KOS entities are modified over time, impacting mappings and potentially...

Non-redundant association rules between diseases and medications: an automated method for knowledge base construction.

BMC medical informatics and decision making
BACKGROUND: The widespread use of electronic health records (EHRs) has generated massive clinical data storage. Association rules mining is a feasible technique to convert this large amount of data into usable knowledge for clinical decision making, ...