Artificial Intelligence Techniques for Business Process Optimization in Cloud-Enabled and Healthcare-Integrated Environments

Authors

  • Leung Ping-kwan USA Author

Keywords:

Artificial Intelligence, Business Process Optimization, Cloud Computing, Healthcare Integration,  Predictive Analytics, Intelligent Automation

Abstract

Business process optimization (BPO) has become increasingly sophisticated with the integration of Artificial Intelligence (AI), particularly in cloud-based infrastructures and healthcare systems. This paper explores the intersection of AI techniques, cloud computing, and healthcare integration to highlight how AI enhances efficiency, scalability, and decision-making in complex business processes. Emphasis is placed on the use of machine learning, intelligent automation, and predictive analytics. Key findings suggest that AI-driven optimization not only improves operational agility but also ensures compliance and better patient outcomes in healthcare contexts.

References

van der Aalst, Wil M. P. Process Mining: Data Science in Action. Springer, 2016.

Kumar, K. (2020). Enhancing interpretability and explainability in deep neural networks for artificial intelligence. QIT Press - International Journal of Artificial Intelligence (QITP-IJAI), 1(1), 1-4.

Russell, Stuart, et al. “Deep Learning for Healthcare Workflow Optimization.” IEEE Access, vol. 6, 2018, pp. 54410–54420.

Subramanyam, S.V. (2025). Cloud-based enterprise systems: Bridging scalability and security in healthcare and finance. International Journal on Science and Technology (IJSAT), 16(1), 1–20.

Priyadarsini, A. (2024). Advancing the understanding of representation learning in artificial intelligence systems. QIT Press - International Journal of Artificial Intelligence (QITP-IJAI), 5(2), 1-5.

Janiesch, Christian, Patrick Zschech, and Kai Heinrich. “Machine Learning and Business Process Management.” Business & Information Systems Engineering, vol. 63, 2021, pp. 357–365.

Subramanyam, S.V. (2021). Cloud computing and business process re-engineering in financial systems: The future of digital transformation. International Journal of Information Technology and Management Information Systems (IJITMIS), 12(1), 126–143.

Bansal, A. (2020). Predictive modeling and complex system analysis reimagined through deep learning-powered artificial intelligence. QIT Press - International Journal of Artificial Intelligence and Deep Learning Research and Development, 1(1), 1-4.

Davenport, Thomas H., and Rajeev Ronanki. “Artificial Intelligence for the Real World.” Harvard Business Review, Jan.–Feb. 2018.

Sun, Jing, Yifan Wang, and Fang Li. “Federated Learning for Cloud-Integrated Healthcare.” Journal of Medical Systems, vol. 47, no. 2, 2023, pp. 1–13.

Navya, M. (2024). Deep learning as the foundation for advanced cognitive automation and human-machine collaboration in artificial intelligence. QIT Press - International Journal of Artificial Intelligence and Deep Learning Research and Development, 5(2), 1-4.

Subramanyam, S.V. (2025). Revolutionizing enterprise workflows: The role of declarative rules in business process systems. International Journal of Information Technology and Management Information Systems (IJITMIS), 16(2), 341–365.

Topol, Eric. Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books, 2019.

Esteva, Andre, Alexandre Robicquet, Bharath Ramsundar, et al. “A Guide to Deep Learning in Healthcare.” Nature Medicine, vol. 25, no. 1, 2019, pp. 24–29.

Subramanyam, S.V. (2023). The intersection of cloud, AI, and IoT: A pre-2021 framework for healthcare business process transformation. International Journal of Cloud Computing (IJCC), 1(1), 53–69.

Ghosh, Ratan, Somnath Ghosh, and Suman Das. “Cloud-Based Healthcare System Using AI and Big Data Analytics.” Journal of King Saud University – Computer and Information Sciences, vol. 34, no. 6, 2020, pp. 3032–3043.

Syed, Abdul Azeem, and Diego M. López. “A Systematic Review of Machine Learning Techniques for Medical Diagnosis.” Journal of Medical Systems, vol. 45, no. 2, 2021, pp. 1–14.

Obermeyer, Ziad, Brian Powers, Christine Vogeli, and Sendhil Mullainathan. “Dissecting Racial Bias in an Algorithm Used to Manage the Health of Populations.” Science, vol. 366, no. 6464, 2019, pp. 447–453.

Subramanyam, S.V. (2024). Transforming financial systems through robotic process automation and AI: The future of smart finance. International Journal of Artificial Intelligence Research and Development (IJAIRD), 2(1), 203–223.

Pan, Jie, and Yiming Zhang. “AI and Cloud Computing for Healthcare: Challenges and Opportunities.” IEEE Access, vol. 10, 2022, pp. 45987–46001.

Dastin, Jeffrey. “Amazon Scraps Secret AI Recruiting Tool That Showed Bias Against Women.” Reuters, 10 Oct. 2018.

Zhang, Zhen, Yong Zhao, and Meikang Qiu. “Trustworthy AI for Healthcare: Federated Learning with Differential Privacy.” ACM Transactions on Internet Technology, vol. 23, no. 3, 2023, pp. 1–21

Downloads

Published

2025-05-03

How to Cite

Leung Ping-kwan. (2025). Artificial Intelligence Techniques for Business Process Optimization in Cloud-Enabled and Healthcare-Integrated Environments. International Journal of Artificial Intelligence, 6(3), 1-7. https://ijai.in/index.php/home/article/view/IJAI_06_03_001