Rate the Article: Leveraging AI in ETL / ELT Designs for Enhanced Health Risk Assessment, IJSR, Call for Papers, Online Journal
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064

Downloads: 6 | Views: 219 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1

Research Paper | Health and Medical Sciences | United States of America | Volume 13 Issue 8, August 2024 | Rating: 4.8 / 10


Leveraging AI in ETL / ELT Designs for Enhanced Health Risk Assessment

Gokul Ramadoss


Abstract: Integrating Artificial Intelligence (AI) into Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes is revolutionizing healthcare data management. This paper explores the importance of ETL/ELT in healthcare and demonstrates how AI enhances data processing efficiency, improves health outcomes, and supports real-time data integration, predictive analytics, and comprehensive risk evaluation. AI-powered ETL/ELT systems facilitate faster, more accurate, and scalable health risk assessments, ultimately enhancing patient care and resource utilization.


Keywords: AI, ETL, ELT, healthcare data integration, health risk assessment, predictive analytics, automation, scalability, patient care, data processing


Edition: Volume 13 Issue 8, August 2024,


Pages: 262 - 265



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