AIMC Topic: Natural Language Processing

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Natural language inference for curation of structured clinical registries from unstructured text.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Clinical registries-structured databases of demographic, diagnosis, and treatment information-play vital roles in retrospective studies, operational planning, and assessment of patient eligibility for research, including clinical trials. R...

A systematic review on natural language processing systems for eligibility prescreening in clinical research.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We conducted a systematic review to assess the effect of natural language processing (NLP) systems in improving the accuracy and efficiency of eligibility prescreening during the clinical research recruitment process.

Ontology-Based Natural Language Processing of Social Media Data in the Assessment of Health Information Sought During Pregnancy.

Studies in health technology and informatics
This study analyzed collected social media data from South Korea containing keywords related to "pregnancy" using ontology-based natural language processing. Of the 504,725 documents, those containing concepts related to "maternal emotion" were the m...

Realizing the Power of Text Mining and Natural Language Processing for Analyzing Patient Safety Event Narratives: The Challenges and Path Forward.

Journal of patient safety
Patient safety event (PSE) reports are a useful lens to understand hazards and patient safety risks in healthcare systems. However, patient safety officers and analysts in healthcare systems and safety organizations are challenged to make sense of th...

Development and Validation of a Natural Language Processing Algorithm to Extract Descriptors of Microbial Keratitis From the Electronic Health Record.

Cornea
PURPOSE: The purpose of this article was to develop and validate a natural language processing (NLP) algorithm to extract qualitative descriptors of microbial keratitis (MK) from electronic health records.

A Machine Learning Approach to Reclassifying Miscellaneous Patient Safety Event Reports.

Journal of patient safety
BACKGROUND AND OBJECTIVES: Medical errors are a leading cause of death in the United States. Despite widespread adoption of patient safety reporting systems to address medical errors, making sense of the reports collected in these systems is challeng...

Extracting social determinants of health from electronic health records using natural language processing: a systematic review.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Social determinants of health (SDoH) are nonclinical dispositions that impact patient health risks and clinical outcomes. Leveraging SDoH in clinical decision-making can potentially improve diagnosis, treatment planning, and patient outcom...

Automated Modeling of Clinical Narrative with High Definition Natural Language Processing Using Solor and Analysis Normal Form.

Studies in health technology and informatics
OBJECTIVE: One important concept in informatics is data which meets the principles of Findability, Accessibility, Interoperability and Reusability (FAIR). Standards, such as terminologies (findability), assist with important tasks like interoperabili...