Patient Perceptions of Artificial Intelligence in Breast Disease Management: A Cross-Sectional Survey in China (Preprint)

BACKGROUND Artificial intelligence (AI) tools are increasingly integrated into healthcare, yet patient perceptions—particularly in breast disease management—remain underexplored. Understanding these attitudes is critical for optimizing AI implementation and addressing disparities in trust and acceptance. OBJECTIVE To assess patient attitudes toward AI tools in breast disease management and identify how age, gender, and education influence willingness to adopt AI in clinical settings in China. METHODS A cross-sectional, online, questionnaire-based survey was conducted among patients who underwent surgery for breast diseases in the Department of Breast Surgery at Peking Union Medical College Hospital (PUMCH) through the wenjuanxing application (a survey platform) from March to May 2025. Of 530 invited participants, 457 (response rate: 86.2%) completed the questionnaire, which evaluated prior AI use, trust levels, concerns, and willingness to engage with AI tools. Primary outcomes included perceptions of AI utility, trust in AI versus physician recommendations, privacy concerns, and willingness to use AI for pre-diagnosis, triage, and clinical decision support. RESULTS Among participants, 91.7% found AI tools at least "somewhat helpful," though 67.5% cited lack of emotional support as a key drawback. When AI and physician advice conflicted, 50.8% fully trusted doctors, while 43.3% preferred integrating both. Willingness to use AI was high for pre-diagnosis (86.0%) and precise triage (92.1%), but lower for clinical diagnosis and treatment assistance (69.9%). Patients across different age groups and educational levels hold generally similar views on AI tools, yet distinct tendencies emerge among subgroups. Ordinal multinomial logistic regression revealed that patients aged over 45 tended to hold more negative evaluations of AI tools, whereas younger individuals showed more positive attitudes. Meanwhile, those with postgraduate education or above also expressed more favorable assessments of AI tools. CONCLUSIONS Patients in this survey demonstrated strong acceptance of AI in breast disease management, but concerns about emotional support, privacy, and accuracy persist. Demographic variations highlight the need for tailored implementation strategies, including transparency protocols and equitable design.