Wang Huike, Ye Zichen, Zhang Peiyu, Cui Xiaoli, Chen Mingyang, Wu Aiyuan, Riggs Sara Lu, Xue Peng, Qiao Youlin
School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Department of Systems and Information Engineering, University of Virginia, Charlottesville, VA, USA.
Digit Health. 2024 Sep 5;10:20552076241279952. doi: 10.1177/20552076241279952. eCollection 2024 Jan-Dec.
The objective of this study was to assess the attitudes toward the Colposcopic Artificial Intelligence Auxiliary Diagnostic System (CAIADS) of colposcopists working in mainland China.
A questionnaire was developed to collect participants' sociodemographic information and assess their awareness, attitudes, and acceptance toward the CAIADS.
There were 284 respondents from 24 provinces across mainland China, with 55% working in primary care institutions. Participant data were divided into two subgroups based on their colposcopy case load per year (i.e. ≥50 cases; <50 cases). The analysis showed that participants with higher loads had more experience working with CAIADS and were more knowledgeable about CAIADS and AI systems. Overall, in both groups, about half of the participants understood the potential applications of big data and AI-assisted diagnostic systems in medicine. Although less than one-third of the participants were knowledgeable about CAIADS and its latest developments, more than 90% of the participants were open with the idea of using CAIADS.
While a related lack of acknowledgement of CAIADS exists, the participants in general had an open attitude toward CAIADS. Practical experience with colposcopy or CAIADS contributed to participants' awareness and positive attitudes. The promotion of AI tools like CAIADS could help address regional health inequities to improve women's well-being, especially in low- and middle-income countries.
本研究旨在评估中国大陆从事阴道镜检查工作的医生对阴道镜人工智能辅助诊断系统（CAIADS）的态度。
设计了一份问卷，以收集参与者的社会人口统计学信息，并评估他们对CAIADS的认知、态度和接受程度。
来自中国大陆24个省份的284名受访者参与了调查，其中55%在基层医疗机构工作。根据参与者每年的阴道镜检查病例数量（即≥50例；<50例）将参与者数据分为两个亚组。分析表明，病例数量较多的参与者使用CAIADS的经验更丰富，对CAIADS和人工智能系统的了解也更多。总体而言，两组中约一半的参与者了解大数据和人工智能辅助诊断系统在医学中的潜在应用。虽然不到三分之一的参与者了解CAIADS及其最新进展，但超过90%的参与者对使用CAIADS持开放态度。
虽然对CAIADS存在相关认知不足，但参与者总体上对CAIADS持开放态度。阴道镜检查或CAIADS的实践经验有助于提高参与者的认知和积极态度。推广像CAIADS这样的人工智能工具有助于解决地区卫生不平等问题，改善妇女健康，特别是在低收入和中等收入国家。
