A newly published systematic review in Cureus spotlights AI as a critical enabler for protecting sensitive data in healthcare environments. The paper, showcased a Systematic Review and Future Research Perspectives on the healthcare environments is authored by Pratik Kasralikar, Omkar Reddy Polu, Balaiah Chamarthi, Rana Veer Samara Sihman Bharattej Rupavath, Sandipkumar Patel, and Ramakrishna Tumati.
With healthcare systems worldwide increasingly adopting artificial intelligence (AI) for diagnostics, treatment planning, and patient monitoring, concerns about data privacy, security, and interoperability have grown more urgent. This comprehensive review, following the rigorous PRISMA guidelines, examines how AI can help mitigate these challenges, providing both theoretical frameworks and practical recommendations.
The authors evaluated findings from multiple peer-reviewed studies across major databases including IEEE Xplore, Scopus, Web of Science, and PubMed. Their analysis demonstrates Artificial Intelligence's effectiveness in enabling decentralized data sharing mechanisms, ensuring data integrity, and improving the transparency and trustworthiness of AI algorithms. If widely adopted, these technologies could safeguard healthcare data for hundreds of millions of patients globally, saving the U.S. healthcare system alone an estimated $20 billion annually in cybersecurity costs, inefficiencies, and data breach recovery.
“This publication arrives at a crucial moment when trust in healthcare AI is directly tied to patient safety and innovation,” said Felix Kramer, Correspondent and Senior Journalist at Alpine Vision Media. “By integrating artificial intelligence in healthcare, the authors offer a powerful strategy to rebuild that trust through technological transparency and security.” While the review confirms AI's vast potential, it also highlights significant challenges—particularly regarding scalability, technical standardization, interoperability, and regulatory compliance. The quality assessment of existing studies revealed moderate-to-high methodological rigor but identified gaps in reproducibility and real-world implementation, pointing toward fertile ground for future interdisciplinary research and development.
Healthcare innovators around the world, such as Dr. Samuel Mwangi of Kenyatta University Hospital in Kenya and Dr. Mariana González of the National Autonomous University of Mexico, have long advocated for decentralized digital health infrastructures. The findings of this review bolster their calls for AI adoption as a critical pillar in the next generation of medical systems, especially in emerging economies where centralized health IT infrastructures are less robust. The collective work of the authors stands as a strategic framework for moving beyond proof-of-concept studies and toward scalable, ethical, and patient-centered AI integration. Their focus on hybrid architectures, clinical trials, and cross-sector collaboration provides a roadmap for researchers and healthcare leaders alike.
“The path to securing healthcare’s AI future isn’t just technical—it’s ethical, collaborative, and forward-thinking,” Kramer added, “This systematic review illuminates that path with precision and depth.” The publication represents a vital contribution to the evolving dialogue on safeguarding digital health ecosystems—one where patients, providers, and policymakers must converge to realize the promise of intelligent, secure, and equitable healthcare.
Reference: DOI 10.7759/cureus.83136
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