Transformative AI in Biomedicine Analysis

Abstract

This chapter provides a comprehensive review of artificial intelligence (AI) applications in biomedicine, highlighting the transformative impact on various domains, from basic research to clinical practice. The author explores AI's role in medical imaging and diagnostics, drug discovery and development, genomics and precision medicine, and healthcare management and delivery. Key advancements, such as deep learning for image analysis, virtual screening for drug design, and AI-driven patient stratification, are discussed. The chapter also addresses challenges surrounding AI implementation, including data access, bias, scalability, transparency, privacy, and regulatory uncertainties. Potential solutions and policy options to address these challenges and enhance AI's benefits are proposed. The author emphasizes the importance of collaboration between AI experts and healthcare stakeholders, as well as the need for responsible AI development practices. Future directions highlight the potential for AI to transform healthcare and improve patient outcomes and need for responsible AI.

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