AIMC Topic: Confidentiality

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A novel fuzzy logic-based image steganography method to ensure medical data security.

Computers in biology and medicine Oct 27, 2015
This study aims to secure medical data by combining them into one file format using steganographic methods. The electroencephalogram (EEG) is selected as hidden data, and magnetic resonance (MR) images are also used as the cover image. In addition to...
Confidentiality Image Interpretation, Computer-Assisted Information Storage and Retrieval Computer Security Humans Algorithms Electronic Health Records Reproducibility of Results Sensitivity and Specificity Logistic Models Fuzzy Logic
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Creation of a new longitudinal corpus of clinical narratives.

Journal of biomedical informatics Oct 1, 2015
The 2014 i2b2/UTHealth Natural Language Processing (NLP) shared task featured a new longitudinal corpus of 1304 records representing 296 diabetic patients. The corpus contains three cohorts: patients who have a diagnosis of coronary artery disease (C...
Electronic Health Records Female Aged Male Middle Aged Risk Assessment Humans Confidentiality Data Mining Computer Security Vocabulary, Controlled Diabetes Complications Boston Comorbidity Incidence Cohort Studies Narration Natural Language Processing Coronary Artery Disease
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A context-aware approach for progression tracking of medical concepts in electronic medical records.

Journal of biomedical informatics Sep 30, 2015
Electronic medical records (EMRs) for diabetic patients contain information about heart disease risk factors such as high blood pressure, cholesterol levels, and smoking status. Discovering the described risk factors and tracking their progression ov...
Male Cardiovascular Diseases Middle Aged Risk Assessment Disease Progression Comorbidity Incidence Cohort Studies Longitudinal Studies Taiwan Narration Natural Language Processing Humans Electronic Health Records Female Aged Diabetes Complications Confidentiality Data Mining Pattern Recognition, Automated Computer Security Vocabulary, Controlled
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Hidden Markov model using Dirichlet process for de-identification.

Journal of biomedical informatics Sep 25, 2015
For the 2014 i2b2/UTHealth de-identification challenge, we introduced a new non-parametric Bayesian hidden Markov model using a Dirichlet process (HMM-DP). The model intends to reduce task-specific feature engineering and to generalize well to new da...
Narration Natural Language Processing Confidentiality Machine Learning Computer Security Computer Simulation Data Mining Vocabulary, Controlled Markov Chains Electronic Health Records Newfoundland and Labrador Pattern Recognition, Automated Cohort Studies Models, Statistical
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Comparison of UMLS terminologies to identify risk of heart disease using clinical notes.

Journal of biomedical informatics Sep 12, 2015
The second track of the 2014 i2b2 challenge asked participants to automatically identify risk factors for heart disease among diabetic patients using natural language processing techniques for clinical notes. This paper describes a rule-based system ...
Confidentiality Data Mining Incidence Pattern Recognition, Automated Cohort Studies Humans Terminology as Topic Longitudinal Studies Electronic Health Records Unified Medical Language System Narration Aged Female Natural Language Processing Computer Security Male Coronary Artery Disease Vocabulary, Controlled Middle Aged Diabetes Complications Risk Assessment Ohio Comorbidity
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A hybrid model for automatic identification of risk factors for heart disease.

Journal of biomedical informatics Sep 12, 2015
Coronary artery disease (CAD) is the leading cause of death in both the UK and worldwide. The detection of related risk factors and tracking their progress over time is of great importance for early prevention and treatment of CAD. This paper describ...
Comorbidity Incidence Cohort Studies Longitudinal Studies Narration Natural Language Processing Female Aged Male Middle Aged Risk Assessment Vocabulary, Controlled Coronary Artery Disease Humans Confidentiality Electronic Health Records Data Mining United Kingdom Pattern Recognition, Automated Computer Security
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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...
Humans Electronic Health Records Female Aged Male Data Mining Incidence Pattern Recognition, Automated Cohort Studies Computer Security Longitudinal Studies Vocabulary, Controlled Narration Diabetes Complications Cardiovascular Diseases Natural Language Processing Middle Aged Confidentiality Risk Assessment Comorbidity China
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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,...
Cardiovascular Diseases Longitudinal Studies Humans Pattern Recognition, Automated Narration Middle Aged Computer Security Electronic Health Records Natural Language Processing Risk Assessment Female Vocabulary, Controlled Confidentiality Comorbidity Aged Diabetes Complications Data Mining Incidence New South Wales Male Cohort 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...
Documentation Pattern Recognition, Automated Computer Security Vocabulary, Controlled Cohort Studies Electronic Health Records Narration Natural Language Processing Confidentiality Data Mining
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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...
Humans Electronic Health Records Vocabulary, Controlled Diabetes Complications Comorbidity Incidence Cohort Studies Confidentiality Longitudinal Studies Data Mining Narration Utah Natural Language Processing Female Pattern Recognition, Automated Aged Computer Security Male Cardiovascular Diseases Middle Aged Risk Assessment
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