AIMC Topic: Natural Language Processing

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Advanced literature analysis in a Big Data world.

Annals of the New York Academy of Sciences
Comprehensive data mining of the scientific literature has become an increasing challenge. To address this challenge, Elsevier's Pathway Studio software uses the techniques of natural language processing to systematically extract specific biological ...

Clinical Natural Language Processing in 2015: Leveraging the Variety of Texts of Clinical Interest.

Yearbook of medical informatics
OBJECTIVE: To summarize recent research and present a selection of the best papers published in 2015 in the field of clinical Natural Language Processing (NLP).

Causality patterns and machine learning for the extraction of problem-action relations in discharge summaries.

International journal of medical informatics
Clinical narrative text includes information related to a patient's medical history such as chronological progression of medical problems and clinical treatments. A chronological view of a patient's history makes clinical audits easier and improves q...

Identification of Long Bone Fractures in Radiology Reports Using Natural Language Processing to support Healthcare Quality Improvement.

Applied clinical informatics
BACKGROUND: Important information to support healthcare quality improvement is often recorded in free text documents such as radiology reports. Natural language processing (NLP) methods may help extract this information, but these methods have rarely...

Can multilinguality improve Biomedical Word Sense Disambiguation?

Journal of biomedical informatics
Ambiguity in the biomedical domain represents a major issue when performing Natural Language Processing tasks over the huge amount of available information in the field. For this reason, Word Sense Disambiguation is critical for achieving accurate sy...

Evaluating semantic similarity between Chinese biomedical terms through multiple ontologies with score normalization: An initial study.

Journal of biomedical informatics
BACKGROUND: Semantic similarity estimation significantly promotes the understanding of natural language resources and supports medical decision making. Previous studies have investigated semantic similarity and relatedness estimation between biomedic...

Extractive text summarization system to aid data extraction from full text in systematic review development.

Journal of biomedical informatics
OBJECTIVES: Extracting data from publication reports is a standard process in systematic review (SR) development. However, the data extraction process still relies too much on manual effort which is slow, costly, and subject to human error. In this s...

A New Data Representation Based on Training Data Characteristics to Extract Drug Name Entity in Medical Text.

Computational intelligence and neuroscience
One essential task in information extraction from the medical corpus is drug name recognition. Compared with text sources come from other domains, the medical text mining poses more challenges, for example, more unstructured text, the fast growing of...

Disease named entity recognition by combining conditional random fields and bidirectional recurrent neural networks.

Database : the journal of biological databases and curation
The recognition of disease and chemical named entities in scientific articles is a very important subtask in information extraction in the biomedical domain. Due to the diversity and complexity of disease names, the recognition of named entities of d...