Women's perspectives on integrating artificial intelligence in breast cancer screening services in Abu Dhabi, united Arab Emirates.
Authors
Affiliations (4)
Affiliations (4)
- Public Health Institute, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates.
- Faculty of Medicine, Istanbul Okan University, Istanbul, Turkey.
- Breast Care Center, Tawam Oncology Center, Tawam Hospital, Al Ain, United Arab Emirates.
- Public Health Institute, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates. [email protected].
Abstract
Artificial intelligence (AI) offers opportunities to enhance breast cancer screening by improving diagnostic accuracy and reducing radiologist workload, yet its successful adoption depends on public trust and acceptability. This cross-sectional survey of 562 Emirati women aged 18 years and older in Abu Dhabi explored knowledge, perceptions, and willingness to participate in AI-supported screening. Using a structured, culturally adapted questionnaire, descriptive statistics summarized attitudes and concerns, and logistic regression identified predictors of AI-related knowledge. Most participants (69%) believed AI could improve diagnostic accuracy, although only 11% fully trusted AI without human oversight. Human clinicians remained central to decision-making, with 86% of women preferring physician judgment in cases of conflict between AI and radiologist findings. Willingness to undergo AI-supported screening was high (74%), though concerns about false results (59%) and data misuse (36%) were prevalent. Being a health professional (aOR = 2.76, 95% CI: 1.23-6.43) and having higher knowledge of breast screening methods (aOR = 8.29, 95% CI: 3.98-18.6) were significantly associated with awareness of AI use in breast cancer screening. These findings indicate that while Emirati women show cautious support for AI in breast cancer screening, trust, cultural values, and baseline knowledge are key determinants of acceptance. Public health strategies that emphasize transparent communication, robust data protection, and education on both conventional and AI-assisted screening are essential to promote equitable and ethical integration of AI technologies into cancer control programs.