European Journal of Biology and Medical Science Research (EJBMSR)

EA Journals

AI-Driven Automation of Patient Data Integration in Complex Healthcare Systems

Abstract

The healthcare industry is experiencing a transformative shift through AI-driven automation of patient data integration systems. As healthcare providers grapple with an expanding volume of data from diverse sources, including electronic health records, medical imaging, and wearable devices, the need for sophisticated integration solutions becomes paramount. AI technologies, particularly natural language processing and machine learning algorithms, are revolutionizing how healthcare organizations manage and utilize patient data. These systems enhance clinical decision-making, streamline operational workflows, and ensure regulatory compliance while maintaining robust security measures. The integration of AI-driven solutions promises to improve diagnostic accuracy, treatment planning, and preventive care while reducing administrative burden and operational costs. Through automated validation, intelligent synchronization, and privacy-preserving techniques, healthcare organizations can achieve more efficient and accurate data management while maintaining the highest standards of patient privacy and data security.

Keywords: artificial intelligence automation, clinical decision support, healthcare data integration, healthcare operational efficiency, patient data security

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This work by European American Journals is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License

 

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Email ID: editor.ejbmsr@ea-journals.org
Impact Factor: 7.77
Print ISSN: 2053-406X
Online ISSN: 2053-4078
DOI: https://doi.org/10.37745/ejbmsr.2013

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