Leveraging AI in ETL / ELT Designs for Enhanced Health Risk Assessment
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
How to Cite?: Gokul Ramadoss, "Leveraging AI in ETL / ELT Designs for Enhanced Health Risk Assessment", Volume 13 Issue 8, August 2024, International Journal of Science and Research (IJSR), Pages: 262-265, https://www.ijsr.net/getabstract.php?paperid=SR24802003019, DOI: https://dx.doi.org/10.21275/SR24802003019