AIMC Topic: Electronic Health Records

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Development and Validation of an Algorithm to Identify Nonalcoholic Fatty Liver Disease in the Electronic Medical Record.

Digestive diseases and sciences
BACKGROUND AND AIMS: Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease worldwide. Risk factors for NAFLD disease progression and liver-related outcomes remain incompletely understood due to the lack of computa...

Outcome Prediction in Clinical Treatment Processes.

Journal of medical systems
Clinical outcome prediction, as strong implications for health service delivery of clinical treatment processes (CTPs), is important for both patients and healthcare providers. Prior studies typically use a priori knowledge, such as demographics or p...

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

Computers in biology and medicine
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...

Creation of a new longitudinal corpus of clinical narratives.

Journal of biomedical informatics
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...

Telemedicine as a special case of machine translation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Machine translation is evolving quite rapidly in terms of quality. Nowadays, we have several machine translation systems available in the web, which provide reasonable translations. However, these systems are not perfect, and their quality may decrea...

A context-aware approach for progression tracking of medical concepts in electronic medical records.

Journal of biomedical informatics
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...

Hidden Markov model using Dirichlet process for de-identification.

Journal of biomedical informatics
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...