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AI-Enhanced Data Analytics in Healthcare: Transforming Patient Care Through Cloud-Based Intelligence

Year: 2025
Type: article
Abstract: AI-enhanced cloud-based data analytics represents a transformative force in modern healthcare delivery, fundamentally altering how medical institutions process information, deliver patient care, and optimize operational efficiency. The integration of artificial intelligence technologies with distributed computing infrastructure enables healthcare organizations to extract meaningful insights from vast medical datasets while supporting predictive analytics, precision medicine, and personalized treatment protocols. Machine learning algorithms deployed on cloud platforms demonstrate exceptional capabilities in early disease detection, genomic analysis, and treatment outcome prediction, shifting healthcare delivery from reactive to proactive intervention strategies. Operational excellence emerges through intelligent workflow optimization, patient admission forecasting, and real-time dashboard analytics that enhance clinical decision-making processes and resource allocation efficiency. Data integration frameworks address critical interoperability challenges by establishing standardized protocols for cross-institutional collaboration while maintaining security and compliance standards. Remote monitoring capabilities through IoT device integration and telemedicine platforms expand healthcare accessibility, enable continuous chronic disease management, and provide real-time health trend analysis through wearable technologies. The convergence of these technological advances positions healthcare organizations to deliver more effective, efficient, and personalized medical care while reducing costs and improving population health outcomes across diverse geographic and demographic populations.
DOI: 10.5281/zenodo.16212874
Language: English
Field: Medicine
Open Access status: green
OpenAlex ID: W6893397925
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