AIMC Topic: Natural Language Processing

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The use of natural language processing on pediatric diagnostic radiology reports in the electronic health record to identify deep venous thrombosis in children.

Journal of thrombosis and thrombolysis
Venous thromboembolism (VTE) is a potentially life-threatening condition that includes both deep vein thrombosis (DVT) and pulmonary embolism. We sought to improve detection and reporting of children with a new diagnosis of VTE by applying natural la...

Enhancing Risk Assessment in Patients Receiving Chronic Opioid Analgesic Therapy Using Natural Language Processing.

Pain medicine (Malden, Mass.)
OBJECTIVES: Clinical guidelines for the use of opioids in chronic noncancer pain recommend assessing risk for aberrant drug-related behaviors prior to initiating opioid therapy. Despite recent dramatic increases in prescription opioid misuse and abus...

Automated Extraction of VTE Events From Narrative Radiology Reports in Electronic Health Records: A Validation Study.

Medical care
BACKGROUND: Surveillance of venous thromboembolisms (VTEs) is necessary for improving patient safety in acute care hospitals, but current detection methods are inaccurate and inefficient. With the growing availability of clinical narratives in an ele...

Challenges in adapting existing clinical natural language processing systems to multiple, diverse health care settings.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Widespread application of clinical natural language processing (NLP) systems requires taking existing NLP systems and adapting them to diverse and heterogeneous settings. We describe the challenges faced and lessons learned in adapting an ...

Development of an automated assessment tool for MedWatch reports in the FDA adverse event reporting system.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: As the US Food and Drug Administration (FDA) receives over a million adverse event reports associated with medication use every year, a system is needed to aid FDA safety evaluators in identifying reports most likely to demonstrate causal ...

Using Natural Language Processing to Extract Abnormal Results From Cancer Screening Reports.

Journal of patient safety
OBJECTIVES: Numerous studies show that follow-up of abnormal cancer screening results, such as mammography and Papanicolaou (Pap) smears, is frequently not performed in a timely manner. A contributing factor is that abnormal results may go unrecogniz...

Application of a Natural Language Processing Algorithm to Asthma Ascertainment. An Automated Chart Review.

American journal of respiratory and critical care medicine
RATIONALE: Difficulty of asthma ascertainment and its associated methodologic heterogeneity have created significant barriers to asthma care and research.

BIOSSES: a semantic sentence similarity estimation system for the biomedical domain.

Bioinformatics (Oxford, England)
MOTIVATION: The amount of information available in textual format is rapidly increasing in the biomedical domain. Therefore, natural language processing (NLP) applications are becoming increasingly important to facilitate the retrieval and analysis o...