(untitled) (Western European Journal of Medicine and Medical Science, 2025)
In the development of a comprehensive, secure, artificial intelligence (AI)-based automated integrated management system for medical associations, cybersecurity issues pose significant challenges. As healthcare organizations increasingly adopt AI to streamline operations, improve patient care, and enhance staff performance, ensuring data security becomes paramount. The system’s ability to process sensitive medical data and provide realtime analytics requires stringent protective measures to safeguard against cyber threats. Key cybersecurity concerns include data breaches, unauthorized access, system vulnerabilities, and the risk of AI models being manipulated through adversarial attacks. The integration of various platforms, including patient management systems, electronic health records (EHRs), and medical devices, further complicates the security landscape by increasing the number of potential attack vectors. Robust encryption, multi-factor authentication, secure data storage, and continuous monitoring for unusual activities are necessary to protect patient data integrity and system functionality. This paper discusses the critical cybersecurity challenges in developing a secure AI-driven management platform for medical services, emphasizing the importance of adopting a proactive, multi-layered security framework to mitigate risks while enhancing the quality of patient care and staff efficiency