AIMC Topic: Risk Management

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Knowledge graph and CBR-based approach for automated analysis of bridge operational accidents: Case representation and retrieval.

PloS one
Bridge operational accident analysis is a critical process in bridge operational risk management. It provides valuable knowledge support for responding to newly occurring accidents. However, there are three issues: (1) research specifically focused o...

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...

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...

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...

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...

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...

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 ...

Artificial intelligence in medicine creates real risk management and litigation issues.

Journal of healthcare risk management : the journal of the American Society for Healthcare Risk Management
The next step in the evolution of electronic medical record (EMR) use is the integration of artificial intelligence (AI) into health care. With the benefit of roughly 15 years of electronic medical records (EMR) data from millions of patients, health...

Ontological approach to the knowledge systematization of a toxic process and toxic course representation framework for early drug risk management.

Scientific reports
Various types of drug toxicity can halt the development of a drug. Because drugs are xenobiotics, they inherently have the potential to cause injury. Clarifying the mechanisms of toxicity to evaluate and manage drug safety during drug development is ...