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Research Paper | Information Technology | United States of America | Volume 13 Issue 10, October 2024 | Popularity: 5.2 / 10

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Machine Learning Algorithms for Predictive Quality Assurance in Healthcare in DW ETL Processes

Arun Kumar Ramachandran Sumangala Devi

Abstract: The healthcare sector constantly contains significant amounts of data from various sources, including patient records and clinical trials. Since the early 1980s, data warehousing and Extract, Transform, and Load (ETL) frameworks have been constantly utilized in predictive analytics to make treatment options and personalized patient care decisions. However, the challenge of the continuously increasing amount of data being generated on a daily basis has called for more efficient techniques to analyze data. The focus of this article is to analyze how the advent of machine learning (ML) has revolutionized predictive analytics by developing models and algorithms that allow for the automation of data warehousing and ETL processes. The various ML applications in predictive analytics, from predicting disease occurrence to predicting surgery outcomes, are further discussed. The benefits of ML include the potential to personalize patient care, accelerate drug development, and identify at - risk patients, among others. ML has the potential to revolutionize predictive analytics in the healthcare sector due to the constant evolution and innovation in the technological world.

Keywords: Machine learning, healthcare, predictive analytics, ETL, data warehousing

Edition: Volume 13 Issue 10, October 2024

Pages: 300 - 304

DOI: https://www.doi.org/10.21275/SR241002082647

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