AI and Cloud Computing for Healthcare and Finance: Predictive Analytics and Digital Payments Using Oracle ML
DOI:
https://doi.org/10.15680/IJCTECE.2025.0805006Keywords:
Artificial Intelligence, Machine Learning, Oracle Machine Learning, Predictive Analytics, Healthcare Cloud Architecture, Oracle Cloud Infrastructure, Machine Learning Models, Real-time Data Processing, Patient Care Optimization, Healthcare Data Integration, Cloud-based Healthcare SolutionsAbstract
The adoption of Artificial Intelligence (AI) and Machine Learning (ML) within healthcare analytics has fundamentally transformed the way healthcare organizations predict outcomes, manage resources, and deliver patient-centered care. By leveraging advanced algorithms and data-driven insights, AI and ML enable predictive modeling that can anticipate patient needs, identify potential health risks, and optimize operational workflows, thereby improving clinical efficiency and overall healthcare quality.
Oracle’s Machine Learning (OML) suite, when integrated with Oracle Cloud Infrastructure (OCI), provides a comprehensive and scalable platform for building, training, and deploying sophisticated AI-driven healthcare applications. This integration allows healthcare institutions to process vast and diverse datasets—ranging from electronic health records (EHRs) and laboratory results to imaging and sensor data—while maintaining stringent security and compliance standards, such as HIPAA and GDPR.
This paper presents an in-depth exploration of AI-enabled cloud architectures in healthcare, detailing the critical components, deployment strategies, and practical applications of OML within OCI. It highlights how predictive analytics, powered by AI and ML, can transform healthcare operations by enabling real-time decision-making, improving patient outcomes, and facilitating data-driven insights across clinical and administrative functions. Additionally, the study emphasizes the advantages of cloud-based AI solutions, including scalability, operational efficiency, and integration with existing healthcare systems, offering a blueprint for building robust, intelligent, and secure healthcare platforms.
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