AIMC Topic: Risk Management

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Can Staff Distinguish Falls: Experimental Hypothesis Verification Using Japanese Incident Reports and Natural Language Processing.

Studies in health technology and informatics Jan 1, 2018
Falls are generally classified into two groups in clinical settings in Japan: falls from the same level and falls from one level to another. We verified whether clinical staff could distinguish between these two types of falls by comparing 3,078 free...
Humans Machine Learning Accidental Falls Natural Language Processing Risk Management Japan
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Robotics: Ethics of artificial intelligence.

Nature May 28, 2015
Humans Artificial Intelligence Communication Decision Support Systems, Clinical Robotics Risk Management Healthcare Disparities Pattern Recognition, Automated Research Personnel Public Opinion Diagnosis Symbiosis Weapons
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Enhancing Patient Safety Event Reporting by K-nearest Neighbor Classifier.

Studies in health technology and informatics Jan 1, 2015
Data quality was placed as a major reason for the low utility of patient safety event reporting systems. A pressing need in improving data quality has advanced recent research focus in data entry associated with human factors. The debate on structure...
Machine Learning Patient Safety Decision Support Systems, Clinical United States Risk Management Data Mining Data Accuracy Quality Improvement Pattern Recognition, Automated Medical Errors Meaningful Use
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On Building an Ontological Knowledge Base for Managing Patient Safety Events.

Studies in health technology and informatics Jan 1, 2015
Over the past decade, improving healthcare quality and safety through patient safety event reporting systems has drawn much attention. Unfortunately, such systems are suffering from low data quality, inefficient data entry and ineffective information...
Patient Safety Electronic Health Records Risk Management Knowledge Bases Internationality Biological Ontologies Terminology as Topic Texas Medical Errors
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Automated Classification of Clinical Incident Types.

Studies in health technology and informatics Jan 1, 2015
We consider the task of automatic classification of clinical incident reports using machine learning methods. Our data consists of 5448 clinical incident reports collected from the Incident Information Management System used by 7 hospitals in the sta...
Machine Learning Reproducibility of Results Sensitivity and Specificity Risk Management Bayes Theorem Pattern Recognition, Automated Hospital Information Systems Medical Errors New South Wales
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