Healthcare Transformation through Big Data Analytics and AI: Current Perceptions of Physicians and Patients on AI Applications in UAE and Future Research

Thesis Defence
Healthcare Transformation through Big Data Analytics and AI: Current Perceptions of Physicians and Patients on AI Applications in UAE and Future Research

Tarek Mansour will publicly defend his thesis.

March 20, 2025
11:00-13:00 (CET)
Room B-122 at ESCP Berlin Campus or online via Zoom

Attend the defence

Abstract

Objective: This thesis explores the integration of Big Data Analytics (BDA) and Artificial Intelligence (AI) in healthcare, focusing on their adoption by healthcare professionals and the trust dynamics from the perspective of patients in the United Arab Emirates (UAE). It investigates how these technologies affect healthcare delivery, the factors influencing their acceptance among physicians, and the ethical and trust-related challenges from patients' perspectives, with a comparative analysis to Germany's practices.

Methods: A mixed-method approach was adopted, encompassing systematic literature reviews, qualitative interviews with 12 healthcare professionals in the UAE, and semi-structured interviews with 17 dyslipidemia patients. Comparative insights were drawn from existing literature on Germany's healthcare AI integration. Thematic and content analysis was conducted using NVivo software to extract recurring themes and insights regarding the adoption and trust in AI-based healthcare systems in both countries.

Results: The study reveals multifaceted factors affecting the integration of AI into healthcare. For healthcare professionals in the UAE, key enablers included training, system interoperability, and regulatory support, while barriers comprised lack of AI explainability, ethical concerns, and infrastructure limitations. Comparatively, Germany's success is attributed to robust regulatory frameworks, comprehensive training programs, and advanced healthcare infrastructure. For UAE patients, key themes included transparency of AI operations, concerns about ethics and privacy, the importance of government oversight, the need for robust data security measures, accountability in AI applications, and the necessity for informed consent and enhanced patient education. The comparison underscored Germany's higher public trust and acceptance of AI in healthcare, driven by strong patient-centric approaches and stringent data security laws.

Conclusions: The findings emphasize that successful adoption of AI in healthcare in the UAE requires overcoming both technological and human-centered challenges, with lessons to be learned from Germany's implementation. For healthcare professionals in the UAE, enhancing AI literacy and ensuring system compatibility are crucial, while for patients, building trust in AI involves improving transparency, ensuring robust ethical standards, and bolstering regulatory frameworks. The thesis concludes that a comprehensive approach, incorporating best practices from Germany, is essential for fostering effective and trustworthy AI integration in healthcare in the UAE.

Keywords: Artificial Intelligence, Big Data Analytics, healthcare integration, physician adoption, patient trust, ethical considerations, UAE, Germany, technology acceptance, digital healthcare transformation.

Jury