AIMC Topic: Data Anonymization

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Impact of De-Identification on Clinical Text Classification Using Traditional and Deep Learning Classifiers.

Studies in health technology and informatics Aug 21, 2019
Clinical text de-identification enables collaborative research while protecting patient privacy and confidentiality; however, concerns persist about the reduction in the utility of the de-identified text for information extraction and machine learnin...
Humans Machine Learning Electronic Health Records Deep Learning Confidentiality Data Anonymization
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Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review.

Journal of the American Medical Informatics Association : JAMIA Oct 1, 2018
OBJECTIVE: To conduct a systematic review of deep learning models for electronic health record (EHR) data, and illustrate various deep learning architectures for analyzing different data sources and their target applications. We also highlight ongoin...
Humans Neural Networks, Computer Prognosis Electronic Health Records Deep Learning Data Anonymization Disease
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Community-Acquired Pneumonia Case Validation in an Anonymized Electronic Medical Record-Linked Expert System.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America May 15, 2017
An electronic anonymized patient portal analysis using radiographic reports and admission and discharge diagnoses had sensitivity, specificity, positive predictive value, and negative predictive value of 84.7%, 78.2%, 75%, and 87%, respectively, for ...
Humans Algorithms Anti-Bacterial Agents Electronic Health Records Female Hospitalization Young Adult Adult Sensitivity and Specificity Male Pneumonia Predictive Value of Tests Data Anonymization Expert Systems Radiography, Thoracic Community-Acquired Infections Patient Portals
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De-identification of patient notes with recurrent neural networks.

Journal of the American Medical Informatics Association : JAMIA May 1, 2017
OBJECTIVE: Patient notes in electronic health records (EHRs) may contain critical information for medical investigations. However, the vast majority of medical investigators can only access de-identified notes, in order to protect the confidentiality...
Humans Neural Networks, Computer Electronic Health Records Data Anonymization Datasets as Topic
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Recent Advances in Clinical Natural Language Processing in Support of Semantic Analysis.

Yearbook of medical informatics Aug 13, 2015
OBJECTIVES: We present a review of recent advances in clinical Natural Language Processing (NLP), with a focus on semantic analysis and key subtasks that support such analysis.
Electronic Health Records Natural Language Processing Data Anonymization Data Collection Semantics Coumarins Isocoumarins
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