Anomaly-based threat detection in smart health using machine learning.

Journal: BMC medical informatics and decision making
Published Date: Nov 19, 2024

Abstract

BACKGROUND: Anomaly detection is crucial in healthcare data due to challenges associated with the integration of smart technologies and healthcare. Anomaly in electronic health record can be associated with an insider trying to access and manipulate the data. This article focuses around the anomalies under different contexts.

Authors

  • Muntaha Tabassum
    Department of Computer Science, Bahria University, Islamabad, Pakistan.
  • Saba Mahmood
    Department of Computer Science, Bahria University, Islamabad, Pakistan. smahmood.buic@bahria.edu.pk.
  • Amal Bukhari
    College of Computer Science and Engineering, University of Jeddah, Saudi Arabia.
  • Bader Alshemaimri
    Software Engineering Department, College of Computing and Information Sciences, King Saud University, Riyadh, Saudi Arabia.
  • Ali Daud
    Faculty of Resilience, Rabdan Academy, Abu Dhabi, United Arab Emirates. alimsdb@gmail.com.
  • Fatima Khalique
    Centre of Excellence in Artificial Intelligence COE-AI, Bahria University, Islamabad, Pakistan.

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