A study on advanced AI-Driven continuous compliance monitoring for cybersecurity regulations in healthcare

The threat levels for cyber risk in the health care industry continue to rise, thus requiring enhanced compliance with various standards. New compliance paradigms are far less effective when compared to traditional methods, especially in the area of real-time threat detection and changes in compliance strategies. The purpose of this paper is to discuss continuous monitoring with a particular focus on the adoption of AI in the field. As a result, the challenges that the study addresses concern the current and potential threats to healthcare facilities by presenting an AI-based framework. This research deals with the contemporary and future issues with healthcare cybersecurity and outlines an AI-based regulatory compliance that is used to identify, evaluate, and act on risks. Applied to a mid-sized hospital for illustration purposes in this research, AI can prove to be a solution to compliance issues arising from human error and poor data security in healthcare organizations.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-30
DOI
https://doi.org/10.5281/zenodo.17464580
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

A study on advanced AI-Driven continuous compliance monitoring for cybersecurity regulations in healthcare

Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

A study on advanced AI-Driven continuous compliance monitoring for cybersecurity regulations in healthcare

article en

Abstract

The threat levels for cyber risk in the health care industry continue to rise, thus requiring enhanced compliance with various standards. New compliance paradigms are far less effective when compared to traditional methods, especially in the area of real-time threat detection and changes in compliance strategies. The purpose of this paper is to discuss continuous monitoring with a particular focus on the adoption of AI in the field. As a result, the challenges that the study addresses concern the current and potential threats to healthcare facilities by presenting an AI-based framework. This research deals with the contemporary and future issues with healthcare cybersecurity and outlines an AI-based regulatory compliance that is used to identify, evaluate, and act on risks. Applied to a mid-sized hospital for illustration purposes in this research, AI can prove to be a solution to compliance issues arising from human error and poor data security in healthcare organizations.

Zenodo (CERN European Organization for Nuclear Research)
University of Massachusetts Amherst (US)
No poverty
Openalex Percentile: Top 51%
Artificial Intelligence in Healthcare and Education
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A study on advanced AI-Driven continuous compliance monitoring for cybersecurity regulations in healthcare · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS