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Risk Management

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Machine Learning Systems Applied to Health Data and System.

European journal of health law
The use of machine learning (ML) in medicine is becoming increasingly fundamental to analyse complex problems by discovering associations among different types of information and to generate knowledge for medical decision support. Many regulatory and...

How Might Artificial Intelligence Applications Impact Risk Management?

AMA journal of ethics
Artificial intelligence (AI) applications have attracted considerable ethical attention for good reasons. Although AI models might advance human welfare in unprecedented ways, progress will not occur without substantial risks. This article considers ...

Online evaluation method of coal mine comprehensive level based on FCE.

PloS one
An online evaluation method of coal mine comprehensive level based on Fuzzy Comprehensive Evaluation method (FCE) is proposed. Firstly, following the principles of fairness, systematicness and hierarchy, taking research and development, production, s...

Validating Intelligent Automation Systems in Pharmacovigilance: Insights from Good Manufacturing Practices.

Drug safety
Pharmacovigilance is the science of monitoring the effects of medicinal products to identify and evaluate potential adverse reactions and provide necessary and timely risk mitigation measures. Intelligent automation technologies have a strong potenti...

Evaluating resampling methods and structured features to improve fall incident report identification by the severity level.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: This study aims to improve the classification of the fall incident severity level by considering data imbalance issues and structured features through machine learning.

Artificial Intelligence for Identifying the Prevention of Medication Incidents Causing Serious or Moderate Harm: An Analysis Using Incident Reporters' Views.

International journal of environmental research and public health
The purpose of this study was to describe incident reporters' views identified by artificial intelligence concerning the prevention of medication incidents that were assessed, causing serious or moderate harm to patients. The information identified t...

Natural language processing and machine learning to assist radiation oncology incident learning.

Journal of applied clinical medical physics
PURPOSE: To develop a Natural Language Processing (NLP) and Machine Learning (ML) pipeline that can be integrated into an Incident Learning System (ILS) to assist radiation oncology incident learning by semi-automating incident classification. Our go...

Prediction Performance Comparison of Risk Management and Control Mode in Regional Sites Based on Decision Tree and Neural Network.

Frontiers in public health
The traditional risk management and control mode (RMCM) in regional sites has the defects of low efficiency, high cost, and lack of systematism. Trying to resolve these defects and explore the application possibility of machine learning, a characteri...

Integrating Human Patterns of Qualitative Coding with Machine Learning: A Pilot Study Involving Technology-Induced Error Incident Reports.

Studies in health technology and informatics
The objective of this research was to develop a reproducible method of integrating human patterns of qualitative coding with machine learning. The application of qualitative codes from the technology-induced error and safety literatures to the analys...

Prospective, multicenter validation of the deep learning-based cardiac arrest risk management system for predicting in-hospital cardiac arrest or unplanned intensive care unit transfer in patients admitted to general wards.

Critical care (London, England)
BACKGROUND: Retrospective studies have demonstrated that the deep learning-based cardiac arrest risk management system (DeepCARS™) is superior to the conventional methods in predicting in-hospital cardiac arrest (IHCA). This prospective study aimed t...