Serverless Quantum-AI and Machine Learning Framework for Intelligent Real-Time Healthcare Analytics
DOI:
https://doi.org/10.15680/IJCTECE.2022.0506013Keywords:
Serverless Computing, Quantum Artificial Intelligence, Machine Learning, Real-Time Healthcare Analytics, Predictive Modeling, Intelligent Automation, Cloud ArchitectureAbstract
This paper presents a novel Serverless Quantum-AI and Machine Learning Framework designed to enhance real-time healthcare analytics and decision-making. The proposed architecture integrates quantum computing principles with artificial intelligence and machine learning models to enable high-speed data processing, intelligent automation, and predictive analysis within healthcare ecosystems. By leveraging a serverless cloud environment, the framework ensures scalability, reliability, and cost efficiency while eliminating traditional infrastructure overheads. The integration of quantum algorithms accelerates diagnostic insights and anomaly detection, while machine learning models continuously adapt to dynamic healthcare data streams. This approach empowers healthcare providers with actionable intelligence for clinical workflows, patient monitoring, and resource optimization, contributing to a resilient and data-driven healthcare infrastructure.
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