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Progress in Medical Sciences ISSN: 2577 - 2996
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Progress in Medical Sciences. 2022; 6(1):(196-202)


Data Security in Healthcare with Machine Learning and Biometric Methods: Current Challenges, Solutions, and Future Directions

Kiran Veernapu

Abstract

The healthcare industry is increasingly adopting digital technologies for patient care, management, and research. However, this shift toward electronic health records (EHR), telemedicine, and other digital healthcare solutions presents significant data security challenges. This paper explores the importance of data security in healthcare, identifies key challenges faced by healthcare organizations, and reviews existing solutions to mitigate these risks. Additionally, it discusses emerging trends and future directions for data security in healthcare, including the role of artificial intelligence (AI), blockchain, and regulatory frameworks. The paper aims to provide healthcare organizations, policymakers, and researchers with a comprehensive understanding of the current landscape of healthcare data security and the path forward.