Leveraging Artificial Intelligence and Cloud Computing for Secure Early Diagnosis and Treatment of Medical Disease

Abstract

AI coupled with cloud computing will revolutionize healthcare through smart, scalable, and secure disease detection and management systems. Recent research works have explored how cloud-based AI frameworks improve medical data processing, predictive analytics, and real-time diagnosis based on modern machine learning, deep learning, and hybrid optimization algorithm. These systems enable precision medicine, early disease prediction, and personalized therapy to deal with large-scale health data emanating from IoT devices, biomedical sensors, and electronic health records. In addition, AI-driven cloud infrastructures enhance data accessibility and interoperability and improve cybersecurity while preserving patient privacy and regulatory compliance. Eventually, edge AI and multi-cloud strategies will improve the reliability and speed of healthcare delivery, particularly in resource-constrained, remote, and disaster-prone areas. Furthermore, AI-cloud synergy is unfolding new applications in biomedical engineering, genomics, and medical imaging that assure remarkable enhancement of diagnostic accuracy, better patient outcomes, and healthcare resilience. In summary, converged AI-cloud technologies will bring about smarter, datadriven, and patient-centered healthcare ecosystems.

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