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A hybrid model for automatic identification of risk factors for heart disease.

Journal of biomedical informatics
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...

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

Journal of biomedical informatics
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...

Coronary artery disease risk assessment from unstructured electronic health records using text mining.

Journal of biomedical informatics
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,...

Adapting existing natural language processing resources for cardiovascular risk factors identification in clinical notes.

Journal of biomedical informatics
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...

Mining heart disease risk factors in clinical text with named entity recognition and distributional semantic models.

Journal of biomedical informatics
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...

Risk factor detection for heart disease by applying text analytics in electronic medical records.

Journal of biomedical informatics
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...

Identifying risk factors for heart disease over time: Overview of 2014 i2b2/UTHealth shared task Track 2.

Journal of biomedical informatics
The second track of the 2014 i2b2/UTHealth natural language processing shared task focused on identifying medical risk factors related to Coronary Artery Disease (CAD) in the narratives of longitudinal medical records of diabetic patients. The risk f...

Agile text mining for the 2014 i2b2/UTHealth Cardiac risk factors challenge.

Journal of biomedical informatics
This paper describes the use of an agile text mining platform (Linguamatics' Interactive Information Extraction Platform, I2E) to extract document-level cardiac risk factors in patient records as defined in the i2b2/UTHealth 2014 challenge. The appro...

Reducing the incidence of oxyhaemoglobin desaturation during rapid sequence intubation in a paediatric emergency department.

BMJ quality & safety
OBJECTIVES: Rapid sequence intubation (RSI) is the standard for definitive airway management in emergency medicine. In a video-based study of RSI in a paediatric emergency department (ED), we reported a high degree of process variation and frequent a...

Towards a Food Safety Knowledge Base Applicable in Crisis Situations and Beyond.

BioMed research international
In case of contamination in the food chain, fast action is required in order to reduce the numbers of affected people. In such situations, being able to predict the fate of agents in foods would help risk assessors and decision makers in assessing th...