AIMC Topic: Vocabulary, Controlled

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An automatic system to identify heart disease risk factors in clinical texts over time.

Journal of biomedical informatics Sep 8, 2015
Despite recent progress in prediction and prevention, heart disease remains a leading cause of death. One preliminary step in heart disease prediction and prevention is risk factor identification. Many studies have been proposed to identify risk fact...
Middle Aged Risk Assessment Comorbidity China Incidence Female Aged Male Cardiovascular Diseases Data Mining Pattern Recognition, Automated Computer Security Vocabulary, Controlled Diabetes Complications Cohort Studies Longitudinal Studies Narration Natural Language Processing Confidentiality Humans Electronic Health Records
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Coronary artery disease risk assessment from unstructured electronic health records using text mining.

Journal of biomedical informatics Aug 28, 2015
Coronary artery disease (CAD) often leads to myocardial infarction, which may be fatal. Risk factors can be used to predict CAD, which may subsequently lead to prevention or early intervention. Patient data such as co-morbidities, medication history,...
Pattern Recognition, Automated Computer Security Vocabulary, Controlled Aged Diabetes Complications Narration Humans Male Risk Assessment New South Wales Natural Language Processing Electronic Health Records Cardiovascular Diseases Comorbidity Confidentiality Female Middle Aged Incidence Data Mining Cohort Studies Longitudinal Studies
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Annotating longitudinal clinical narratives for de-identification: The 2014 i2b2/UTHealth corpus.

Journal of biomedical informatics Aug 28, 2015
The 2014 i2b2/UTHealth natural language processing shared task featured a track focused on the de-identification of longitudinal medical records. For this track, we de-identified a set of 1304 longitudinal medical records describing 296 patients. Thi...
Electronic Health Records Data Mining Documentation Cohort Studies Pattern Recognition, Automated Narration Computer Security Natural Language Processing Vocabulary, Controlled Confidentiality
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Adapting existing natural language processing resources for cardiovascular risk factors identification in clinical notes.

Journal of biomedical informatics Aug 28, 2015
The 2014 i2b2 natural language processing shared task focused on identifying cardiovascular risk factors such as high blood pressure, high cholesterol levels, obesity and smoking status among other factors found in health records of diabetic patients...
Incidence Cohort Studies Longitudinal Studies Narration Natural Language Processing Confidentiality Data Mining Utah Pattern Recognition, Automated Computer Security Male Cardiovascular Diseases Middle Aged Risk Assessment Comorbidity Humans Vocabulary, Controlled Electronic Health Records Diabetes Complications Female Aged
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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...
Electronic Health Records China Data Mining Pattern Recognition, Automated Computer Security Vocabulary, Controlled Cohort Studies Narration Natural Language Processing Data Interpretation, Statistical Confidentiality
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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 Cohort Studies Humans Longitudinal Studies Electronic Health Records Models, Statistical Female Narration Aged Male Cardiovascular Diseases Middle Aged Risk Assessment Comorbidity Natural Language Processing Incidence
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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 Middle Aged Risk Assessment Comorbidity Incidence Cohort Studies Electronic Health Records Female Aged Male Cardiovascular Diseases Diabetes Complications Data Mining Pattern Recognition, Automated Longitudinal Studies California Narration Computer Security Natural Language Processing Vocabulary, Controlled Confidentiality
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A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis.

Artificial intelligence in medicine Aug 14, 2015
OBJECTIVE: Case-based reasoning (CBR) is a problem-solving paradigm that uses past knowledge to interpret or solve new problems. It is suitable for experience-based and theory-less problems. Building a semantically intelligent CBR that mimic the expe...
Information Storage and Retrieval Semantics Biological Ontologies Vocabulary, Controlled Algorithms Diagnosis, Computer-Assisted Diabetes Mellitus Fuzzy Logic Humans Artificial Intelligence
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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...
Machine Learning Algorithms Electronic Health Records Information Storage and Retrieval Semantics Vocabulary, Controlled Problem-Based Learning
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Normalizing clinical terms using learned edit distance patterns.

Journal of the American Medical Informatics Association : JAMIA Jul 31, 2015
BACKGROUND: Variations of clinical terms are very commonly encountered in clinical texts. Normalization methods that use similarity measures or hand-coded approximation rules for matching clinical terms to standard terminologies have limited accuracy...
Unified Medical Language System Machine Learning Algorithms Vocabulary, Controlled Natural Language Processing Terminology as Topic
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