AIMC Topic: Electronic Health Records

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Using neural attention networks to detect adverse medical events from electronic health records.

Journal of biomedical informatics Oct 15, 2018
The detection of Adverse Medical Events (AMEs) plays an important role in disease management in ensuring efficient treatment delivery and quality improvement of health services. Recently, with the rapid development of hospital information systems, a ...
Databases, Factual Electronic Health Records Cardiovascular Diseases Hospitals Humans Neural Networks, Computer Algorithms Myocardial Revascularization Hospital Information Systems Hemorrhage Medical Informatics Myocardial Ischemia Deep Learning China Area Under Curve
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Explainable machine-learning predictions for the prevention of hypoxaemia during surgery.

Nature biomedical engineering Oct 10, 2018
Although anaesthesiologists strive to avoid hypoxemia during surgery, reliably predicting future intraoperative hypoxemia is not currently possible. Here, we report the development and testing of a machine-learning-based system that, in real time dur...
Hypoxia Surgical Procedures, Operative Aged, 80 and over Anesthesiologists Female Adult Humans Area Under Curve Middle Aged Risk Factors Male Machine Learning Anesthesia, General ROC Curve Aged Electronic Health Records
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Application of electronic trigger tools to identify targets for improving diagnostic safety.

BMJ quality & safety Oct 5, 2018
Progress in reducing diagnostic errors remains slow partly due to poorly defined methods to identify errors, high-risk situations, and adverse events. Electronic trigger (e-trigger) tools, which mine vast amounts of patient data to identify signals i...
Humans Diagnostic Errors Algorithms Risk Assessment Natural Language Processing Patient Safety Safety Management Electronic Health Records
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Comparison of 2 Natural Language Processing Methods for Identification of Bleeding Among Critically Ill Patients.

JAMA network open Oct 5, 2018
IMPORTANCE: To improve patient safety, health care systems need reliable methods to detect adverse events in large patient populations. Events are often described in clinical notes, rather than structured data, which make them difficult to identify o...
Support Vector Machine Natural Language Processing Hemorrhage Male Middle Aged ROC Curve Machine Learning Aged Critical Illness Aged, 80 and over Electronic Health Records Sensitivity and Specificity Humans Female
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Utilizing soft constraints to enhance medical relation extraction from the history of present illness in electronic medical records.

Journal of biomedical informatics Oct 4, 2018
Relation extraction between medical concepts from electronic medical records has pervasive applications as well as significance. However, previous researches utilizing machine learning algorithms judge the semantic types of medical concept pair menti...
Regression Analysis Humans Probability Reproducibility of Results Medical Informatics China Deep Learning Algorithms Support Vector Machine Electronic Health Records Models, Statistical
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Towards automated clinical coding.

International journal of medical informatics Oct 2, 2018
BACKGROUND: Patients' encounters with healthcare services must undergo clinical coding. These codes are typically derived from free-text notes. Manual clinical coding is expensive, time-consuming and prone to error. Automated clinical coding systems ...
Pattern Recognition, Automated International Classification of Diseases Clinical Coding Humans Neural Networks, Computer Electronic Health Records
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PISTON: Predicting drug indications and side effects using topic modeling and natural language processing.

Journal of biomedical informatics Sep 27, 2018
The process of discovering novel drugs to treat diseases requires a long time and high cost. It is important to understand side effects of drugs as well as their therapeutic effects, because these can seriously damage the patients due to unexpected a...
Drug Repositioning Natural Language Processing Area Under Curve Probability Medical Informatics Algorithms Drug-Related Side Effects and Adverse Reactions Phenotype Electronic Health Records Data Mining Humans Systems Biology
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A Random Forest-Assisted Evolutionary Algorithm for Data-Driven Constrained Multiobjective Combinatorial Optimization of Trauma Systems.

IEEE transactions on cybernetics Sep 26, 2018
Many real-world optimization problems can be solved by using the data-driven approach only, simply because no analytic objective functions are available for evaluating candidate solutions. In this paper, we address a class of expensive data-driven co...
Algorithms Electronic Health Records Humans Machine Learning Decision Trees Wounds and Injuries
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Predicting of anaphylaxis in big data EMR by exploring machine learning approaches.

Journal of biomedical informatics Sep 25, 2018
Anaphylaxis is a life-threatening allergic reaction that occurs suddenly after contact with an allergen. Epidemiological studies about anaphylaxis are very important in planning and evaluating new strategies that prevent this reaction, but also in pr...
Big Data Cluster Analysis Decision Making Linear Models Anaphylaxis Regression Analysis Algorithms Medical Informatics Electronic Health Records Humans Language Neural Networks, Computer Machine Learning
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Is Multiclass Automatic Text De-Identification Worth the Effort?

Methods of information in medicine Sep 24, 2018
OBJECTIVES: Automatic de-identification to remove protected health information (PHI) from clinical text can use a "binary" model that replaces redacted text with a generic tag (e.g., ""), or can use a "multiclass" model that retains more class i...
Humans Algorithms Electronic Health Records Data Anonymization False Positive Reactions
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