Integrating AI and Machine Learning for Enhanced Decision-Making in Healthcare Business Ecosystem

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative technologies in the healthcare business ecosystem, enabling data-driven decision-making and enhancing operational efficiency. This paper explores the integration of AI and ML to address key challenges in healthcare, including patient outcome prediction, resource optimization, fraud detection, and regulatory compliance. By leveraging predictive modeling, clustering, and anomaly detection, this study highlights how AI-driven insights can empower healthcare providers to make informed decisions, reduce costs, and improve patient care quality. Ethical considerations and compliance with regulations such as HIPAA and GDPR are also examined, emphasizing the importance of fairness and transparency in AI applications. The findings underscore the potential of AI and ML to revolutionize healthcare ecosystems by fostering innovation, improving stakeholder collaboration, and ensuring equitable service delivery. This work provides a comprehensive framework for integrating advanced technologies in healthcare operations, paving the way for a more resilient and adaptive system.