Human-AI collaboration in healthcare securit

Healthcare security gets a transformative boost from Artificial Intelligence (AI) implementation which improves patient protections as well as protects healthcare information systems while simultaneously generating operational efficiency. Modern healthcare organizations which depend heavily on digital data systems use AI technologies to develop advanced cybersecurity methods that protect their confidential patient data. Healthcare facilities require real-time artificial intelligence analysis of data volumes together with anomaly detection for their defense against escalating cybersecurity threats in healthcare. Healthcare security benefitted considerably from AI technologies but organizations encounter multiple challenges because AI raises privacy issues in patient data and creates biases within algorithmic decisions while patients depend heavily on automated systems. Computer systems powered by AI face challenges regarding ethical standards because they must demonstrate transparency and accountability whenever they control patient healthcare decisions or security systems. The study investigates the coexistence of humans alongside AI systems in healthcare security by establishing the essentialness of human expertise for handling ethical and legal intricacies of healthcare data security. The paper explains that AI systems need to show transparency along with continual updates and compatibility with traditional security systems but still require human oversight for fair accountability assessments. The paper analyzes AI-human teamwork to provide evidence about best practices for handling AI risks and achieving better patient safety and trust in healthcare.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-30
DOI
https://doi.org/10.5281/zenodo.17192289
Primary Topic
Canadian Policy and Governance
Type
article
Field-Weighted Citation Impact
0.00
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article

Human-AI collaboration in healthcare securit

Zenodo (CERN European Organization for Nuclear Research)
Canadian Policy and Governance
article

Human-AI collaboration in healthcare securit

article en

Abstract

Healthcare security gets a transformative boost from Artificial Intelligence (AI) implementation which improves patient protections as well as protects healthcare information systems while simultaneously generating operational efficiency. Modern healthcare organizations which depend heavily on digital data systems use AI technologies to develop advanced cybersecurity methods that protect their confidential patient data. Healthcare facilities require real-time artificial intelligence analysis of data volumes together with anomaly detection for their defense against escalating cybersecurity threats in healthcare. Healthcare security benefitted considerably from AI technologies but organizations encounter multiple challenges because AI raises privacy issues in patient data and creates biases within algorithmic decisions while patients depend heavily on automated systems. Computer systems powered by AI face challenges regarding ethical standards because they must demonstrate transparency and accountability whenever they control patient healthcare decisions or security systems. The study investigates the coexistence of humans alongside AI systems in healthcare security by establishing the essentialness of human expertise for handling ethical and legal intricacies of healthcare data security. The paper explains that AI systems need to show transparency along with continual updates and compatibility with traditional security systems but still require human oversight for fair accountability assessments. The paper analyzes AI-human teamwork to provide evidence about best practices for handling AI risks and achieving better patient safety and trust in healthcare.

Zenodo (CERN European Organization for Nuclear Research)
University of Central Missouri (US), Judson University (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 40%
Canadian Policy and Governance
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