Smart Healthcare: Integrating Artificial Intelligence for Better Patient Outcomes
DOI:
https://doi.org/10.48001/978-81-966500-0-1-4Keywords:
Machine Learning (ML), Genomic Analysis, Pathology, Disease control systemAbstract
The merging of artificial intelligence (AI) with healthcare in recent years has signaled the beginning of a revolutionary period in patient care and medical practice. The integration of AI technologies in the context of smart healthcare is examined in this chapter, with a focus on how these technologies might improve patient outcomes. We start by describing the basic ideas of artificial intelligence (AI) and how they relate to many aspects of healthcare, such as treatment planning, diagnosis, customized medicine, and operational effectiveness. The topic also includes the latest developments in artificial intelligence (AI) technologies, including predictive analytics, natural language processing, and machine learning algorithms, as well as their useful applications in healthcare environments. A thorough analysis of case studies demonstrates how AI-driven solutions are increasing the precision of diagnoses, enhancing treatment plans, and simplifying administrative procedures. The chapter also discusses the difficulties and constraints associated with integrating AI, such as the need for strong legal frameworks and validation, algorithmic bias, and data privacy issues. We can provide more proactive and individualized patient care by incorporating AI into healthcare systems, which will eventually improve patient outcomes and streamline the delivery of healthcare. This chapter offers a nuanced perspective on the potential of artificial intelligence (AI) to alter healthcare practices through a thorough analysis of current advances and empirical data. It also highlights future prospects for research and development in the field of smart healthcare.
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