AIMC Topic: Electronic Health Records

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Knowledge-Based Query Construction Using the CDSS Knowledge Base for Efficient Evidence Retrieval.

Sensors (Basel, Switzerland) Aug 28, 2015
Finding appropriate evidence to support clinical practices is always challenging, and the construction of a query to retrieve such evidence is a fundamental step. Typically, evidence is found using manual or semi-automatic methods, which are time-con...
Humans Home Care Services Artificial Intelligence Software Knowledge Bases Information Storage and Retrieval MEDLINE Assisted Living Facilities Electronic Health Records Neoplasms Decision Support Systems, Clinical Chronic Disease
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ReCAP: Feasibility and Accuracy of Extracting Cancer Stage Information From Narrative Electronic Health Record Data.

Journal of oncology practice Aug 25, 2015
PURPOSE: Cancer stage, one of the most important prognostic factors for cancer-specific survival, is often documented in narrative form in electronic health records (EHRs). Such documentation results in tedious and time-consuming abstraction efforts ...
Humans Algorithms Electronic Health Records Prognosis Reproducibility of Results Natural Language Processing Neoplasms Neoplasm Staging Neoplasm Metastasis Datasets as Topic
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CRFs based de-identification of medical records.

Journal of biomedical informatics Aug 24, 2015
De-identification is a shared task of the 2014 i2b2/UTHealth challenge. The purpose of this task is to remove protected health information (PHI) from medical records. In this paper, we propose a novel de-identifier, WI-deId, based on conditional rand...
Confidentiality Data Mining Pattern Recognition, Automated Computer Security Vocabulary, Controlled Cohort Studies Narration Natural Language Processing Data Interpretation, Statistical Electronic Health Records China
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Mining heart disease risk factors in clinical text with named entity recognition and distributional semantic models.

Journal of biomedical informatics Aug 21, 2015
We present the design, and analyze the performance of a multi-stage natural language processing system employing named entity recognition, Bayesian statistics, and rule logic to identify and characterize heart disease risk factor events in diabetic p...
Confidentiality Data Mining Semantics Pattern Recognition, Automated Computer Security Vocabulary, Controlled Diabetes Complications Wisconsin Longitudinal Studies Models, Statistical Narration Natural Language Processing Comorbidity Incidence Cohort Studies Humans Male Electronic Health Records Cardiovascular Diseases Female Middle Aged Aged Risk Assessment
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Natural Language Processing and the Promise of Big Data: Small Step Forward, but Many Miles to Go.

Circulation. Cardiovascular quality and outcomes Aug 18, 2015
Humans Electronic Health Records Natural Language Processing
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MELLO: Medical lifelog ontology for data terms from self-tracking and lifelog devices.

International journal of medical informatics Aug 17, 2015
OBJECTIVE: The increasing use of health self-tracking devices is making the integration of heterogeneous data and shared decision-making more challenging. Computational analysis of lifelog data has been hampered by the lack of semantic and syntactic ...
Medical Records Information Storage and Retrieval Biological Ontologies Electronic Health Records Terminology as Topic Republic of Korea Self Care
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Risk factor detection for heart disease by applying text analytics in electronic medical records.

Journal of biomedical informatics Aug 14, 2015
In the United States, about 600,000 people die of heart disease every year. The annual cost of care services, medications, and lost productivity reportedly exceeds 108.9 billion dollars. Effective disease risk assessment is critical to prevention, ca...
Humans Electronic Health Records Female Aged Comorbidity Incidence Cohort Studies Longitudinal Studies Male Cardiovascular Diseases Middle Aged Risk Assessment Vocabulary, Controlled Diabetes Complications Data Mining Pattern Recognition, Automated California Computer Security Narration Natural Language Processing Confidentiality
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Active learning: a step towards automating medical concept extraction.

Journal of the American Medical Informatics Association : JAMIA Aug 7, 2015
OBJECTIVE: This paper presents an automatic, active learning-based system for the extraction of medical concepts from clinical free-text reports. Specifically, (1) the contribution of active learning in reducing the annotation effort and (2) the robu...
Problem-Based Learning Machine Learning Algorithms Electronic Health Records Information Storage and Retrieval Semantics Vocabulary, Controlled
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A systematic comparison of feature space effects on disease classifier performance for phenotype identification of five diseases.

Journal of biomedical informatics Aug 1, 2015
Automated phenotype identification plays a critical role in cohort selection and bioinformatics data mining. Natural Language Processing (NLP)-informed classification techniques can robustly identify phenotypes in unstructured medical notes. In this ...
Reproducibility of Results Sensitivity and Specificity Cardiovascular Diseases Diagnosis, Computer-Assisted Humans Phenotype Electronic Health Records Natural Language Processing Data Mining New York Pattern Recognition, Automated Decision Support Systems, Clinical Diabetes Mellitus Support Vector Machine Obesity
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Medication Extraction from Electronic Clinical Notes in an Integrated Health System: A Study on Aspirin Use in Patients with Nonvalvular Atrial Fibrillation.

Clinical therapeutics Jul 29, 2015
PURPOSE: The purpose of this study was to investigate whether aspirin use can be captured from the clinical notes in a nonvalvular atrial fibrillation population.
Aspirin Delivery of Health Care, Integrated Reproducibility of Results Humans Information Storage and Retrieval Sensitivity and Specificity Algorithms California Natural Language Processing Electronic Health Records Platelet Aggregation Inhibitors Atrial Fibrillation
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