Smart Health Records: Integrating AI for Efficient Data Management

The rapid evolution of healthcare demands innovative solutions for managing the vast quantities of data generated daily. This paper examines the concept of Smart Health Records (SHRs) and their integration with Artificial Intelligence (AI) to improve healthcare delivery. SHRs represent an advanced iteration of electronic health records, equipped with AI-powered tools to ensure real-time data sharing, predictive analytics, and automated administrative processes. AI’s capabilities, including natural language processing, machine learning, and predictive modeling, streamline data management and enhance clinical decision-making. However, the transition to SHRs is not without challenges, such as data privacy, algorithm accuracy, and resistance to technological adoption. This paper discusses best practices for implementing AI-driven SHRs and examines future trends, emphasizing their potential to revolutionize healthcare by fostering patient-centered care, improving efficiency, and enabling personalized medicine. Keywords: Smart Health Records, Artificial Intelligence, Electronic Health Records, Healthcare Data Management, Predictive Analytics

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Publication Details

Journal
NEWPORT INTERNATIONAL JOURNAL OF RESEARCH IN MEDICAL SCIENCES
Published
2025-02-05
DOI
https://doi.org/10.59298/nijrms/2025/6.1.141800
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
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article

Smart Health Records: Integrating AI for Efficient Data Management

Nicole Arnold
NEWPORT INTERNATIONAL JOURNAL OF RESEARCH IN MEDICAL SCIENCES
Machine Learning in Healthcare
article

Smart Health Records: Integrating AI for Efficient Data Management

Nicole Arnold
article en

Abstract

The rapid evolution of healthcare demands innovative solutions for managing the vast quantities of data generated daily. This paper examines the concept of Smart Health Records (SHRs) and their integration with Artificial Intelligence (AI) to improve healthcare delivery. SHRs represent an advanced iteration of electronic health records, equipped with AI-powered tools to ensure real-time data sharing, predictive analytics, and automated administrative processes. AI’s capabilities, including natural language processing, machine learning, and predictive modeling, streamline data management and enhance clinical decision-making. However, the transition to SHRs is not without challenges, such as data privacy, algorithm accuracy, and resistance to technological adoption. This paper discusses best practices for implementing AI-driven SHRs and examines future trends, emphasizing their potential to revolutionize healthcare by fostering patient-centered care, improving efficiency, and enabling personalized medicine. Keywords: Smart Health Records, Artificial Intelligence, Electronic Health Records, Healthcare Data Management, Predictive Analytics

NEWPORT INTERNATIONAL JOURNAL OF RESEARCH IN MEDICAL SCIENCESVol. 6(1)
Openalex Percentile: Top 99%
Machine Learning in Healthcare
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