数字原生代对皮肤癌诊断移动人工智能应用的偏好研究卡塔尔世界杯8强波胆分析调查研究%A haggenm ller,Sarah %A Krieghoff-Henning,Eva %A Jutzi,Tanja %A Trapp,Nicole %A Kiehl,Lennard %A Utikal,Jochen Sven %A Fabian,Sascha %A Brinker,Titus Josef %+肿瘤数字生物标志物组，德国癌症研究中心国家肿瘤疾病中心，Im Neuenheimer Feld 280，海德堡，69120，德国，49 6221 32 19 304，titus.brinker@dkfz.de %K人工智能%K皮肤癌%K皮肤癌筛查%K诊断%K数字原生生物%K接受%K关注%K偏好%K在线调查%D 2021 %7 27.8.2021 %9背景:人工智能(AI)已经显示出改善各种疾病诊断的潜力，特别是在皮肤癌的早期发现方面。研究尚未调查人工智能技术在临床实践中的明确应用，或确定对年轻用户群体的附加价值。基于人工智能的诊断工具的翻译只有在被潜在用户接受的情况下才能成功。作为数字原住民的年轻人可能为成功将人工智能应用于临床实践提供了最大的潜力，同时，他们也代表了未来一代皮肤癌筛查的参与者。目的:我们进行了一项匿名在线调查，以了解个人愿意接受基于人工智能的皮肤癌诊断移动应用程序的方式和程度。我们评估了偏好和关注点的相对影响，重点是年轻年龄组。方法:我们通过三种社交媒体渠道(facebook、LinkedIn和Xing)招募35岁以下的参与者。通过描述性分析和统计检验来评估参与者对皮肤检查移动应用程序的态度。 We integrated an adaptive choice-based conjoint to assess participants’ preferences. We evaluated potential concerns using maximum difference scaling. Results: We included 728 participants in the analysis. The majority of participants (66.5%, 484/728; 95% CI 0.631-0.699) expressed a positive attitude toward the use of AI-based apps. In particular, participants residing in big cities or small towns (P=.02) and individuals that were familiar with the use of health or fitness apps (P=.02) were significantly more open to mobile diagnostic systems. Hierarchical Bayes estimation of the preferences of participants with a positive attitude (n=484) revealed that the use of mobile apps as an assistance system was preferred. Participants ruled out app versions with an accuracy of ≤65%, apps using data storage without encryption, and systems that did not provide background information about the decision-making process. However, participants did not mind their data being used anonymously for research purposes, nor did they object to the inclusion of clinical patient information in the decision-making process. Maximum difference scaling analysis for the negative-minded participant group (n=244) showed that data security, insufficient trust in the app, and lack of personal interaction represented the dominant concerns with respect to app use. Conclusions: The majority of potential future users below 35 years of age were ready to accept AI-based diagnostic solutions for early detection of skin cancer. However, for translation into clinical practice, the participants’ demands for increased transparency and explainability of AI-based tools seem to be critical. Altogether, digital natives between 18 and 24 years and between 25 and 34 years of age expressed similar preferences and concerns when compared both to each other and to results obtained by previous studies that included other age groups. %M 34448722 %R 10.2196/22909 %U https://mhealth.www.mybigtv.com/2021/8/e22909 %U https://doi.org/10.2196/22909 %U http://www.ncbi.nlm.nih.gov/pubmed/34448722