Independent Researcher, USA.
World Journal of Advanced Engineering Technology and Sciences, 2025, 15(03), 1182–1189
Article DOI: 10.30574/wjaets.2025.15.3.1044
Received on 01 May 2025; revised on 10 June 2025; accepted on 12 June 2025
The integration of cloud analytics and artificial intelligence in healthcare represents a transformative paradigm shift that revolutionizes medical practice through advanced diagnostic capabilities and patient monitoring systems. Cloud-based AI solutions leverage sophisticated computational infrastructure to process vast amounts of medical data, enabling healthcare providers to identify pathological conditions at their earliest stages while significantly improving patient outcomes and reducing healthcare costs. The convergence of deep learning architectures, particularly convolutional neural networks and transformer models, with cloud computing platforms creates powerful medical image analysis systems that exceed traditional diagnostic accuracy levels. Real-time health monitoring through Internet of Medical Things devices and wearable sensors facilitates continuous patient surveillance and predictive analytics, enabling proactive healthcare interventions before critical situations develop. Fast Healthcare Interoperability Resources standards and robust data integration frameworks ensure seamless data exchange across diverse healthcare information systems while maintaining the highest levels of security and privacy protection. Implementation challenges encompass technical complexities, regulatory compliance requirements, and organizational change management, necessitating comprehensive planning and substantial investment in infrastructure, training, and ongoing system maintenance to achieve successful deployment and operation in clinical environments.
Cloud Analytics; Artificial Intelligence; Medical Image Analysis; Predictive Healthcare Monitoring; Healthcare Data Integration
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Jawahar Ravee Nithianandam. Advanced cloud analytics and artificial intelligence in healthcare: Medical image analysis for early disease detection and patient health monitoring. World Journal of Advanced Engineering Technology and Sciences, 2025, 15(03), 1182-1189. Article DOI: 10.30574/wjaets.2025.15.3.1044.