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Risk Management

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Ethicara for Responsible AI in Healthcare: A System for Bias Detection and AI Risk Management.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The increasing torrents of health AI innovations hold promise for facilitating the delivery of patient-centered care. Yet the enablement and adoption of AI innovations in the healthcare and life science industries can be challenging with the rising c...

A navigational risk evaluation of ferry transport: Continuous risk management matrix based on fuzzy Best-Worst Method.

PloS one
Ferry transport has witnessed numerous fatal accidents due to unsafe navigation; thus, it is of paramount importance to mitigate risks and enhance safety measures in ferry navigation. This paper aims to evaluate the navigational risk of ferry transpo...

Safety improvement requires data: the case for automation and artificial intelligence during incident reporting.

British journal of anaesthesia
The reporting of incidents has a long association with safety in healthcare and anaesthesia, yet many incident reporting systems substantially under-report critical events. Better understanding the underlying reasons for low levels of critical incide...

Proposing an AI Passport as a Mitigating Action of Risk Associated to Artificial Intelligence in Healthcare.

Studies in health technology and informatics
The integration of Artificial Intelligence (AI) in healthcare signifies a substantial shift, offering benefits to patients and healthcare systems while also introducing new risks. The emphasis on patient safety and performance standards is pivotal, e...

Managing workplace AI risks and the future of work.

American journal of industrial medicine
Artificial intelligence (AI)-the field of computer science that designs machines to perform tasks that typically require human intelligence-has seen rapid advances in the development of foundation systems such as large language models. In the workpla...

Risk management of patients with multiple CVDs: what are the best practices?

Expert review of cardiovascular therapy
INTRODUCTION: Managing patients with multiple risk factors for CVDs can present distinct challenges for healthcare providers, therefore addressing them can be paramount to optimize patient care.

Advancing enterprise risk management with deep learning: A predictive approach using the XGBoost-CNN-BiLSTM model.

PloS one
Enterprise risk management is a key element to ensure the sustainable and steady development of enterprises. However, traditional risk management methods have certain limitations when facing complex market environments and diverse risk events. This s...

Radiation oncology at crossroads: Rise of AI and managing the unexpected.

Journal of applied clinical medical physics
Integrating artificial intelligence (AI) into radiation oncology has revolutionized clinical workflows, enhancing efficiency, safety, and quality. However, this transformation comes with a price of increased complexity and the emergence of unpredicta...

Integrating enterprise risk management to address AI-related risks in healthcare: Strategies for effective risk mitigation and implementation.

Journal of healthcare risk management : the journal of the American Society for Healthcare Risk Management
The incorporation of artificial intelligence (AI) in health care offers revolutionary enhancements in patient diagnostics, clinical processes, and overall access to services. Nevertheless, this technological transition brings forth various new, intri...

Exploring Suitability of Low-Severity Rating Hospital Incident Reports for Machine Learning.

Computers, informatics, nursing : CIN
Electronic incident reporting is a key quality and a safety process for healthcare organizations that assists in evaluating performance and informing quality improvement initiatives. Although it is mandatory for high-severity incident reports to be i...