摘要目的:探讨中国医学影像人工智能（AI）发展现状，为AI的发展提供数据支持。方法:2022年5月，中华医学会放射学分会和中国医学影像AI产学研用创新联盟携手以调查问卷形式在全国发起中国医学影像AI应用现状和发展需求调研。本次调研分别围绕医学影像AI临床应用、企业发展以及在高校的教育需求等面向不同人群开展，并进行描述性统计分析。结果:中国医学影像AI在临床应用、企业发展及教育教学方面取得了长足发展。临床应用方面，90.8%（5 765/6 347）的调查者对AI有了初步以上的了解，62.1%（3 798/6 119）的医师表示科室中已经有医学影像AI产品的应用，AI产品目前已经在医学影像检查全流程中展开应用，尤其是辅助诊断，肺结节AI筛查应用占比达到89.5%（3 401/3 798）。制约医学影像AI快速发展的主要因素为人才缺乏［47.3%（3 002/6 347）］、数据质量低［45.7%（2 898/6 347）］和产品功能不完善［40.4%（2 566/6 347）］。企业方面，规模在100人以下占比为65.4%（17/26），规模在100人以上的企业占比为34.6%（9/26），企业当前主要的使用对象面向二级以上医院，占比约92.3%（24/26）。教育方面，不同层次学校目前开展的AI课程、实践操作以及讲座的数量和质量各不相同，其中硕博士AI课程开设最多，占比约22.5%（86/381），而针对专科生、本科生及规培生开设AI课程占比均小于15%，超过60%学生均表示学校有必要加开AI类课程，其中硕博士对加开AI类课程需求最大［84.8%（323/381）］。结论:中国医学影像AI发展及普及继续繁荣向好，机遇与挑战并存，要坚持临床需求为导向，实现临床应用、企业发展及教育教学的协同发展。

abstractsObjective:To explore the current status of the artificial intelligence (AI) developments in medical imaging in China, and to provide data for the development of AI.Methods:In May 2022, the Radiology Branch of the Chinese Medical Association and the China Medical Imaging AI Industry-University-Research Innovation Alliance jointly launched a nationwide survey on the application status and development needs of medical imaging AI in China in the form of a questionnaire. This survey was carried out for different groups of people, focusing on the clinical applications of medical imaging AI, enterprise development, and educational needs in colleges and universities, with the descriptive statistical analysis performed.Results:China′s medical imaging AI has made great progress in clinical applications, in enterprise developments, as well as in the education and teaching areas. In terms of clinical application, 90.8% (5 765/6 347) of the survey respondents had a preliminary understanding of AI. There were 62.1% (3 798/6 119) doctors confirmed the applications medical imaging AI products in their departments. AI products were applied in the whole process of medical imaging examination, especially in assistance of the diagnosis. The application of pulmonary nodules screening accounted for 89.5% (3 401/3 798) of all medical imaging AIs. The main factors restricting the rapid development of medical imaging AI included lack of experts [47.3% (3 002/6 347)], poor data quality [45.7% (2 898/6 347)] and imperfect function of the products [40.4% (2 566/6 347)]; in terms of enterprises, there were 65.4% enterprises with a scale of less than 100 employees (17/26), and 34.6% with a scale of more than 100 employees (9/26). The main group of the customers were the hospitals above the second level, accounting for about 92.3% (24/26); in terms of education, the number and quality of AI courses, practical operations and lectures currently carried out by schools vary between different levels. The AI courses for graduated students accounted for about 22.5% (86/381), which were the largest in number; while the proportion of AI courses for junior college students, undergraduates and regular trainees were less than 15%. More than 60% of the students thought it necessary for schools to establish AI courses. Among all the students, the master′s and doctoral candidates had the greatest demand for additional AI courses [84.8% (323/381)].Conclusions:The development and popularization of medical imaging AI in China continues to prosper, with opportunities and challenges coexisting. It is necessary to adhere to the orientation of clinical needs, and to realize the coordinated development of clinical application, enterprise development, as well as education and teaching.