Rongali, Sateesh Kumar and Varri, Durga Bramarambika Sailaja (2025) Human-AI collaboration in healthcare security. World Journal of Advanced Research and Reviews, 25 (3). pp. 2111-2116. ISSN 2581-9615
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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.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/wjarr.2025.25.3.0553 |
Uncontrolled Keywords: | Algorithmic Bias; Artificial Intelligence (AI); Cybersecurity; Data Privacy; Ethical Considerations; Healthcare Security; Machine Learning (ML); Threat Detection |
Depositing User: | Editor WJARR |
Date Deposited: | 22 Jul 2025 15:36 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/1469 |