AIMC Topic: Natural Language Processing

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An unsupervised and customizable misspelling generator for mining noisy health-related text sources.

Journal of biomedical informatics
BACKGROUND: Data collection and extraction from noisy text sources such as social media typically rely on keyword-based searching/listening. However, health-related terms are often misspelled in such noisy text sources due to their complex morphology...

CIBS: A biomedical text summarizer using topic-based sentence clustering.

Journal of biomedical informatics
Automatic text summarizers can reduce the time required to read lengthy text documents by extracting the most important parts. Multi-document summarizers should produce a summary that covers the main topics of multiple related input texts to diminish...

Natural language processing-based assessment of consistency in summaries of product characteristics of generic antimicrobials.

Pharmacology research & perspectives
To investigate consistency in summaries of product characteristics (SmPCs) of generic antimicrobials, we used natural language processing (NLP) to analyze and compare large amounts of text quantifying consistency between original and generic SmPCs. W...

Automated Extraction of Diagnostic Criteria From Electronic Health Records for Autism Spectrum Disorders: Development, Evaluation, and Application.

Journal of medical Internet research
BACKGROUND: Electronic health records (EHRs) bring many opportunities for information utilization. One such use is the surveillance conducted by the Centers for Disease Control and Prevention to track cases of autism spectrum disorder (ASD). This pro...

SIFR annotator: ontology-based semantic annotation of French biomedical text and clinical notes.

BMC bioinformatics
BACKGROUND: Despite a wide adoption of English in science, a significant amount of biomedical data are produced in other languages, such as French. Yet a majority of natural language processing or semantic tools as well as domain terminologies or ont...

A method of inferring the relationship between Biomedical entities through correlation analysis on text.

Biomedical engineering online
BACKGROUND: One of the most important processes in a machine learning-based natural language processing is to represent words. The one-hot representation that has been commonly used has a large size of vector and assumes that the features that make u...

Word and Sentence Embedding Tools to Measure Semantic Similarity of Gene Ontology Terms by Their Definitions.

Journal of computational biology : a journal of computational molecular cell biology
The gene ontology (GO) database contains GO terms that describe biological functions of genes. Previous methods for comparing GO terms have relied on the fact that GO terms are organized into a tree structure. Under this paradigm, the locations of tw...

Ground Glass Lesions on Chest Imaging: Evaluation of Reported Incidence in Cancer Patients Using Natural Language Processing.

The Annals of thoracic surgery
BACKGROUND: Ground glass opacities (GGOs) on computed tomography (CT) have gained significant recent attention, with unclear incidence and epidemiologic patterns. Natural language processing (NLP) is a powerful computing tool that collects variables ...

Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances.

Journal of biomedical informatics
The importance of incorporating Natural Language Processing (NLP) methods in clinical informatics research has been increasingly recognized over the past years, and has led to transformative advances. Typically, clinical NLP systems are developed and...

Psychiatric stressor recognition from clinical notes to reveal association with suicide.

Health informatics journal
Suicide takes the lives of nearly a million people each year and it is a tremendous economic burden globally. One important type of suicide risk factor is psychiatric stress. Prior studies mainly use survey data to investigate the association between...