AIMC Topic: Natural Language Processing

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Building longitudinal medication dose data using medication information extracted from clinical notes in electronic health records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To develop an algorithm for building longitudinal medication dose datasets using information extracted from clinical notes in electronic health records (EHRs).

Using Natural Language Processing on Electronic Health Records to Enhance Detection and Prediction of Psychosis Risk.

Schizophrenia bulletin
BACKGROUND: Using novel data mining methods such as natural language processing (NLP) on electronic health records (EHRs) for screening and detecting individuals at risk for psychosis.

Predicting Discharge Disposition Following Meningioma Resection Using a Multi-Institutional Natural Language Processing Model.

Neurosurgery
BACKGROUND: Machine learning (ML)-based predictive models are increasingly common in neurosurgery, but typically require large databases of discrete variables for training. Natural language processing (NLP) can extract meaningful data from unstructur...

Applying natural language processing and machine learning techniques to patient experience feedback: a systematic review.

BMJ health & care informatics
OBJECTIVES: Unstructured free-text patient feedback contains rich information, and analysing these data manually would require a lot of personnel resources which are not available in most healthcare organisations.To undertake a systematic review of t...

Can reproducibility be improved in clinical natural language processing? A study of 7 clinical NLP suites.

Journal of the American Medical Informatics Association : JAMIA
BACKGROUND: The increasing complexity of data streams and computational processes in modern clinical health information systems makes reproducibility challenging. Clinical natural language processing (NLP) pipelines are routinely leveraged for the se...

Natural language processing to measure the frequency and mode of communication between healthcare professionals and family members of critically ill patients.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To apply natural language processing (NLP) techniques to identify individual events and modes of communication between healthcare professionals and families of critically ill patients from electronic medical records (EMR).