Affiliation:
1. Amity Business School, Amity University, Noida, India
2. Delhi Technical Campus, India
3. Sharda School of Business Studies, Sharda University, India
Abstract
This chapter examines the transformative potential of machine learning in shaping smart health services within the framework of Industry 5.0. Through a comprehensive exploration of applications, methodologies, and real-world case studies, this chapter illustrates how machine learning algorithms are revolutionizing healthcare services. From real-time data analytics to personalized treatment pathways, the integration of machine learning empowers healthcare practitioners to make informed decisions that drive efficiency, accuracy, and patient-centred care. The chapter highlights the symbiotic relationship between machine learning and Industry 5.0, showcasing how data-driven insights and real-time collaboration are fostering the evolution of smart health services. As healthcare transitions from reactive to proactive, this chapter envisions a future where machine learning-driven smart health services not only optimize processes but also enhance patient well-being, marking a transformative step toward a patient-centric, technologically empowered future.
Reference41 articles.
1. A machine learning model for improving healthcare services on cloud computing environment
2. Ahmad, M. A., Eckert, C., & Teredesai, A. (2018). Interpretable machine learning in healthcare. Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, 559-560.
3. Artificial Intelligence in Industry 5.0: The Next Revolution in Productivity and Working Conditions.;A. S.Ahuja;International Journal of Research and Analytical Reviews,2020
4. BoxG. E.JenkinsG. M.ReinselG. C. (1994). Time Series Analysis: Forecasting and Control. John Wiley & Sons.
5. BrownL.MillerC. (2020). Ethical and Legal Considerations of AI in Healthcare. HealthTech Magazine.