Abstract
This study explores the integration of machine learning, blockchain technology, and regulatory frameworks in biomedical cybersecurity. It highlights the potential of machine learning in enhancing biomedical device and healthcare information system security, while blockchain technology is crucial for ensuring security, integrity, and privacy in healthcare data management. The study also examines the global regulatory framework for biological cybersecurity, identifying challenges, gaps, and best practices. The analysis includes case studies, effective integration strategies, and future research directions. The report concludes with a synthesis of best practices and suggestions, offering valuable insights for policymakers, healthcare practitioners, and technology developers in the field of biomedical cybersecurity.
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