AIMC Topic: Language

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Spoken words as biomarkers: using machine learning to gain insight into communication as a predictor of anxiety.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The goal of this study was to explore whether features of recorded and transcribed audio communication data extracted by machine learning algorithms can be used to train a classifier for anxiety.

Advancing PICO element detection in biomedical text via deep neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: In evidence-based medicine, defining a clinical question in terms of the specific patient problem aids the physicians to efficiently identify appropriate resources and search for the best available evidence for medical treatment. In order...

Ontologies for Liver Diseases Representation: A Systematic Literature Review.

Journal of digital imaging
Ontology, as a useful knowledge engineering technique, has been widely used for reducing ambiguity and helping with information sharing. It is considered originally to be clear, comprehensive, and with well-defined format. It characterizes several do...

Automated Misspelling Detection and Correction in Persian Clinical Text.

Journal of digital imaging
Accurate electronic health records are important for clinical care, research, and patient safety assurance. Correction of misspelled words is required to ensure the correct interpretation of medical records. In the Persian language, the lack of autom...

Pre-trained language model augmented adversarial training network for Chinese clinical event detection.

Mathematical biosciences and engineering : MBE
Clinical event detection (CED) is a hot topic and essential task in medical artificial intelligence, which has attracted the attention from academia and industry over the recent years. However, most studies focus on English clinical narratives. Owing...

BioBERT: a pre-trained biomedical language representation model for biomedical text mining.

Bioinformatics (Oxford, England)
MOTIVATION: Biomedical text mining is becoming increasingly important as the number of biomedical documents rapidly grows. With the progress in natural language processing (NLP), extracting valuable information from biomedical literature has gained p...

Quantifying the Association Between Psychotherapy Content and Clinical Outcomes Using Deep Learning.

JAMA psychiatry
IMPORTANCE: Compared with the treatment of physical conditions, the quality of care of mental health disorders remains poor and the rate of improvement in treatment is slow, a primary reason being the lack of objective and systematic methods for meas...

The influence of place and time on lexical behavior: A distributional analysis.

Behavior research methods
We measured and documented the influence of corpus effects on lexical behavior. Specifically, we used a corpus of over 26,000 fiction books to show that computational models of language trained on samples of language (i.e., subcorpora) representative...

NimbleMiner: A Novel Multi-Lingual Text Mining Application.

Studies in health technology and informatics
This demonstration showcase will present a novel open access text mining application called NimbleMiner. NimbleMiner's architecture is language agnostic and it can be potentially applied in multiple languages. The system was applied in a series of re...