Abstract
This meta-analysis offers a comprehensive review of the literature surrounding the integration of Artificial Intelligence (AI) in healthcare. Drawing upon an extensive array of scholarly articles, research papers, and industry reports, this study synthesizes the current state of knowledge regarding AI's applications, challenges, and future directions within the healthcare sector. The analysis encompasses various dimensions of AI implementation, including diagnostic assistance, treatment optimization, patient management, and administrative streamlining. Additionally, it examines the methodological approaches employed in AI healthcare research, assessing the efficacy and reliability of AI-driven interventions across diverse medical domains. Furthermore, this meta-analysis explores the ethical, legal, and social implications associated with AI adoption in healthcare, shedding light on issues of data privacy, algorithmic bias, and patient autonomy. Through a systematic examination of existing literature, this study elucidates key trends, knowledge gaps, and emerging research directions in the evolving intersection of AI and healthcare, providing valuable insights for policymakers, practitioners, and researchers alike.
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