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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...

Application of Artificial Intelligence or machine learning in risk sharing agreements for pharmacotherapy risk management.

Journal of integrative bioinformatics
Applications of Artificial Intelligence in medical informatics solutions risk sharing have social value. At a time of ever-increasing cost for the provision of medicines to citizens, there is a need to restrain the growth of health care costs. The se...

The use of natural language processing in detecting and predicting falls within the healthcare setting: a systematic review.

International journal for quality in health care : journal of the International Society for Quality in Health Care
Falls are a common problem associated with significant morbidity, mortality, and economic costs. Current fall prevention policies in local healthcare settings are often guided by information provided by fall risk assessment tools, incident reporting,...

External Validation of Deep Learning-Based Cardiac Arrest Risk Management System for Predicting In-Hospital Cardiac Arrest in Patients Admitted to General Wards Based on Rapid Response System Operating and Nonoperating Periods: A Single-Center Study.

Critical care medicine
OBJECTIVES: The limitations of current early warning scores have prompted the development of deep learning-based systems, such as deep learning-based cardiac arrest risk management systems (DeepCARS). Unfortunately, in South Korea, only two instituti...

Machine learning in internet financial risk management: A systematic literature review.

PloS one
Internet finance has permeated into myriad households, bringing about lifestyle convenience alongside potential risks. Presently, internet finance enterprises are progressively adopting machine learning and other artificial intelligence methods for r...

Managing risk and resilience in autonomous and intelligent systems: Exploring safety in the development, deployment, and use of artificial intelligence in healthcare.

Risk analysis : an official publication of the Society for Risk Analysis
Autonomous and intelligent systems (AIS) are being developed and deployed across a wide range of sectors and encompass a variety of technologies designed to engage in different forms of independent reasoning and self-directed behavior. These technolo...

An integrated approach to occupational health risk assessment of manufacturing nanomaterials using Pythagorean Fuzzy AHP and Fuzzy Inference System.

Scientific reports
Nanomaterials (NMs) have the potential to be hazardous owing to their unique physico-chemical properties. Therefore, the need for Health Risk Assessment (HRA) of NMs is expanding. In this study, a novel HRA was developed by the Pythagorean Fuzzy Heal...

A novel decision support system for proactive risk management in healthcare based on fuzzy inference, neural network and support vector machine.

International journal of medical informatics
BACKGROUND: The nature of activities practiced in healthcare organizations makes risk management the most crucial issue for decision-makers, especially in developing countries. New technologies provide effective solutions to support engineers in mana...

Analysis of Critical Incident Reports Using Natural Language Processing.

Studies in health technology and informatics
UNLABELLED: A Critical Incident Reporting System (CIRS) collects anecdotal reports from employees, which serve as a vital source of information about incidents that could potentially harm patients.

A method for managing scientific research project resource conflicts and predicting risks using BP neural networks.

Scientific reports
This study begins by considering the resource-sharing characteristics of scientific research projects to address the issues of resource misalignment and conflict in scientific research project management. It comprehensively evaluates the tangible and...