How to Manage Big Data in Healthcare and what are Automated Machine Learning Tools in this case Introduction of a powerful Medical Registry and Data Analysis Platform as automated machine learning tool

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Isham Alzoubi

School of Surveying Geospatial Engineering, Syria

: J Comput Eng Inf Technol

Abstract

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Introduction: Big data has revolutionized the healthcare industry, enabling healthcare providers to collect and analyze vast amounts of data to improve patient outcomes. However, managing big data in healthcare can be challenging due to the complexity and variety of data sources. Automated machine learning tools have emerged as a promising solution to help healthcare organizations (HO) manage big data effectively. Based on the needs of HO’s a powerful medical registry and data analysis platform is created and will be introduced. Method: This research paper aims to explore how to manage big data in healthcare and the role of automated machine learning tools in this case. The study utilizes a literature review and case studies to identify the best practices for managing big data in healthcare and the benefits of automated machine learning tools. Result: The literature review and case studies reveal several best practices for managing big data in healthcare, including data standardization, data quality management, and data governance. Automated machine learning tools can help healthcare organizations automate these processes and improve the accuracy and efficiency of data analysis. Additionally, machine learning tools can enhance clinical decision-making and enable personalized medicine. The new medical registry platform will be used to demonstrate the latter.

Biography

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PhD-Candidate in Artificial Intelligence and Advanced Technology in Business Management, Healthcare & Business Administration, Clinical Informatician, Scientific Researcher, International Consultant, Advisor, Coach, part-time motivational speaker. A professional with an international master’s degree in clinical informatics, Master of philosophy in Business Administration. Furthermore, eHealth- Master Advanced Health Informatics, Health Economics- Executive Master Evidence Based Practice-Epidemiology, Software Engineering, Programming, Artificial Intelligence and Robotics, Master’s in Business & Healthcare Management and Leadership.