AI and resilient cloud infrastructure in healthcare

The transformative convergence of artificial intelligence and resilient cloud infrastructure within healthcare environments represents a fundamental shift in medical service delivery, data management, and patient care administration. The digital evolution occurring across healthcare institutions has established new frameworks for handling clinical information at unprecedented scale and complexity. Cloud infrastructure provides the foundation through multi-tier architectures that balance security requirements with accessibility needs, while sophisticated storage frameworks accommodate the exponential growth in diverse clinical data types. Interoperability standards facilitate seamless data exchange across previously siloed systems, creating comprehensive patient records that enable holistic analytics. AI integration enhances patient care through predictive analytics that identify deterioration risks before clinical manifestation, diagnostic support systems that analyze medical images with remarkable precision, and treatment optimization frameworks that recommend personalized intervention strategies. Resilient system design incorporating high-availability architectures, robust cybersecurity frameworks, and comprehensive disaster recovery protocols ensures continuous operation even during infrastructure challenges. Looking forward, edge computing deployments and federated learning approaches promise to further enhance system capabilities, while evolving regulatory frameworks emphasize algorithmic transparency and validation methodologies.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-31
DOI
https://doi.org/10.5281/zenodo.17365308
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

AI and resilient cloud infrastructure in healthcare

Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

AI and resilient cloud infrastructure in healthcare

article en

Abstract

The transformative convergence of artificial intelligence and resilient cloud infrastructure within healthcare environments represents a fundamental shift in medical service delivery, data management, and patient care administration. The digital evolution occurring across healthcare institutions has established new frameworks for handling clinical information at unprecedented scale and complexity. Cloud infrastructure provides the foundation through multi-tier architectures that balance security requirements with accessibility needs, while sophisticated storage frameworks accommodate the exponential growth in diverse clinical data types. Interoperability standards facilitate seamless data exchange across previously siloed systems, creating comprehensive patient records that enable holistic analytics. AI integration enhances patient care through predictive analytics that identify deterioration risks before clinical manifestation, diagnostic support systems that analyze medical images with remarkable precision, and treatment optimization frameworks that recommend personalized intervention strategies. Resilient system design incorporating high-availability architectures, robust cybersecurity frameworks, and comprehensive disaster recovery protocols ensures continuous operation even during infrastructure challenges. Looking forward, edge computing deployments and federated learning approaches promise to further enhance system capabilities, while evolving regulatory frameworks emphasize algorithmic transparency and validation methodologies.

Zenodo (CERN European Organization for Nuclear Research)
Film Independent (US)
Openalex Percentile: Top 52%
Artificial Intelligence in Healthcare and Education
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AI and resilient cloud infrastructure in healthcare · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS