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eISSN: 2581-9615 || CODEN (USA): WJARAI || Impact Factor: 8.2 || ISSN Approved Journal

Human-AI collaboration in healthcare security

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  • Human-AI collaboration in healthcare security

Sateesh Kumar Rongali * and Durga Bramarambika Sailaja Varri

Judson University 1151 N State St, Elgin, IL 60123* and University of Central Missouri, 108 W South St, Warrensburg, MO 64093, US.

Review Article

World Journal of Advanced Research and Reviews, 2025, 25(03), 2505-2510

Article DOI: 10.30574/wjarr.2025.25.3.0562

DOI url: https://doi.org/10.30574/wjarr.2025.25.3.0562

Received on 18 February 2025; revised on 22 March 2025; accepted on 25 March 2025

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.

Algorithmic Bias; Artificial Intelligence (AI); Cybersecurity; Data Privacy; Ethical Considerations; Healthcare Security; Machine Learning (ML); Threat Detection

https://journalwjarr.com/sites/default/files/fulltext_pdf/WJARR-2025-0562.pdf

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Sateesh Kumar Rongali and Durga Bramarambika Sailaja Varri. Human-AI collaboration in healthcare security. World Journal of Advanced Research and Reviews, 2025, 25(03), 2505-2510. Article DOI: https://doi.org/10.30574/wjarr.2025.25.3.0562.

Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0

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