AIMC Topic: Natural Language Processing

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Mapping Phenotypic Information in Heterogeneous Textual Sources to a Domain-Specific Terminological Resource.

PloS one
Biomedical literature articles and narrative content from Electronic Health Records (EHRs) both constitute rich sources of disease-phenotype information. Phenotype concepts may be mentioned in text in multiple ways, using phrases with a variety of st...

The use of natural language processing on narrative medication schedules to compute average weekly dose.

Pharmacoepidemiology and drug safety
PURPOSE: Medications with non-standard dosing and unstandardized units of measurement make the estimation of prescribed dose difficult from pharmacy dispensing data. A natural language processing tool named the SIG extractor was developed to identify...

Gene Ontology synonym generation rules lead to increased performance in biomedical concept recognition.

Journal of biomedical semantics
BACKGROUND: Gene Ontology (GO) terms represent the standard for annotation and representation of molecular functions, biological processes and cellular compartments, but a large gap exists between the way concepts are represented in the ontology and ...

A Part-Of-Speech term weighting scheme for biomedical information retrieval.

Journal of biomedical informatics
In the era of digitalization, information retrieval (IR), which retrieves and ranks documents from large collections according to users' search queries, has been popularly applied in the biomedical domain. Building patient cohorts using electronic he...

Automated detection of discourse segment and experimental types from the text of cancer pathway results sections.

Database : the journal of biological databases and curation
Automated machine-reading biocuration systems typically use sentence-by-sentence information extraction to construct meaning representations for use by curators. This does not directly reflect the typical discourse structure used by scientists to con...

Training and evaluation corpora for the extraction of causal relationships encoded in biological expression language (BEL).

Database : the journal of biological databases and curation
Success in extracting biological relationships is mainly dependent on the complexity of the task as well as the availability of high-quality training data. Here, we describe the new corpora in the systems biology modeling language BEL for training an...

The Markyt visualisation, prediction and benchmark platform for chemical and gene entity recognition at BioCreative/CHEMDNER challenge.

Database : the journal of biological databases and curation
Biomedical text mining methods and technologies have improved significantly in the last decade. Considerable efforts have been invested in understanding the main challenges of biomedical literature retrieval and extraction and proposing solutions to ...

Mining biomedical images towards valuable information retrieval in biomedical and life sciences.

Database : the journal of biological databases and curation
Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous ...

Predicting Social Anxiety Treatment Outcome Based on Therapeutic Email Conversations.

IEEE journal of biomedical and health informatics
Predicting therapeutic outcome in the mental health domain is of utmost importance to enable therapists to provide the most effective treatment to a patient. Using information from the writings of a patient can potentially be a valuable source of inf...

Gaining insights from social media language: Methodologies and challenges.

Psychological methods
Language data available through social media provide opportunities to study people at an unprecedented scale. However, little guidance is available to psychologists who want to enter this area of research. Drawing on tools and techniques developed in...