AIMC Topic: Electronic Health Records
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Entity recognition from clinical texts via recurrent neural network.
BMC medical informatics and decision making
Jul 5, 2017
BACKGROUND: Entity recognition is one of the most primary steps for text analysis and has long attracted considerable attention from researchers. In the clinical domain, various types of entities, such as clinical entities and protected health inform...
Detecting clinically relevant new information in clinical notes across specialties and settings.
BMC medical informatics and decision making
Jul 5, 2017
BACKGROUND: Automated methods for identifying clinically relevant new versus redundant information in electronic health record (EHR) clinical notes is useful for clinicians and researchers involved in patient care and clinical research, respectively....
A Novel Approach towards Medical Entity Recognition in Chinese Clinical Text.
Journal of healthcare engineering
Jul 5, 2017
Medical entity recognition, a basic task in the language processing of clinical data, has been extensively studied in analyzing admission notes in alphabetic languages such as English. However, much less work has been done on nonstructural texts that...
A comparison of rule-based and machine learning approaches for classifying patient portal messages.
International journal of medical informatics
Jun 23, 2017
OBJECTIVE: Secure messaging through patient portals is an increasingly popular way that consumers interact with healthcare providers. The increasing burden of secure messaging can affect clinic staffing and workflows. Manual management of portal mess...
Update: healthcare reform - it's getting personal.
Personalized medicine
Jun 22, 2017
Natural Language Processing for Asthma Ascertainment in Different Practice Settings.
The journal of allergy and clinical immunology. In practice
Jun 19, 2017
BACKGROUND: We developed and validated NLP-PAC, a natural language processing (NLP) algorithm based on predetermined asthma criteria (PAC) for asthma ascertainment using electronic health records at Mayo Clinic.
Text Mining of the Electronic Health Record: An Information Extraction Approach for Automated Identification and Subphenotyping of HFpEF Patients for Clinical Trials.
Journal of cardiovascular translational research
Jun 5, 2017
Precision medicine requires clinical trials that are able to efficiently enroll subtypes of patients in whom targeted therapies can be tested. To reduce the large amount of time spent screening, identifying, and recruiting patients with specific subt...
Automated problem list generation and physicians perspective from a pilot study.
International journal of medical informatics
Jun 4, 2017
OBJECTIVE: An accurate, comprehensive and up-to-date problem list can help clinicians provide patient-centered care. Unfortunately, problem lists created and maintained in electronic health records by providers tend to be inaccurate, duplicative and ...
De-identification of clinical notes via recurrent neural network and conditional random field.
Journal of biomedical informatics
Jun 1, 2017
De-identification, identifying information from data, such as protected health information (PHI) present in clinical data, is a critical step to enable data to be shared or published. The 2016 Centers of Excellence in Genomic Science (CEGS) Neuropsyc...
The effects of natural language processing on cross-institutional portability of influenza case detection for disease surveillance.
Applied clinical informatics
May 31, 2017
OBJECTIVES: This study evaluates the accuracy and portability of a natural language processing (NLP) tool for extracting clinical findings of influenza from clinical notes across two large healthcare systems. Effectiveness is evaluated on how well NL...
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