Leveraging Networked Artificial Intelligence for Healthcare Transformation

Abstract

The integration of Artificial Intelligence (AI) in healthcare has signified the starting of a new era of innovation, with improved diagnostic accuracy, personalized treatment plans, and operational efficiency. This chapter investigates how networked AI systems, defined as interconnected AI models that analyze and process healthcare data from multiple sources, can lead to significant modifications in patient care, diagnosis, treatment, and operational efficiency. This chapter describes the technical architecture of AI, challenges associated with AI, including data security and privacy, computational cost, and the necessity for unbiased frameworks. Ethical and legal aspects of decentralized data processing are discussed with a focus on methodologies for ensuring compliance with global health data regulations. This chapter gives a detailed overview of the present state and possible future directions of AI in healthcare. It aspires to guide researchers, practitioners, and policymakers in grasping its complete potential for improved health outcomes and medical enhancements.

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