Preparedness of European pediatric oncologists to integrate AI in the clinical routine

Alberto E. Tozzi , Diana Ferro , Ileana Croci , Francesco Fabozzi , Angela Mastronuzzi
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Abstract

Background

Artificial intelligence (AI) holds promise in pediatric oncology, yet its full potential faces challenges. We undertook a survey aimed at assessing the viewpoints of European pediatric oncologists delving into their perceptions and expectations regarding the potential influence of AI in their clinical workflows.

Method

We conducted a survey by means of four hypothetical scenarios using AI and the Shinners Artificial Intelligence Perception (SHAIP) tool to assess healthcare professionals' perceptions of AI in pediatric oncology. We performed multinomial logistic regression to explore associations of responses to clinical scenarios with age and SHAIP scores.

Results

We obtained 140 responses and the analysis was performed on 108. The SHAIP questionnaire mean total score was 3.29 (SD 0.93) for the professional impact, and 2.37 (SD 0.61) for preparedness. Regarding the clinical scenarios, 34.9 % of respondents would ask for a procedure for confirming their diagnosis in case of discrepancy between AI decision support and human diagnosis; 55.8 % would be concerned about the generalizability an AI decision support system in case of lack of data from certain geographic areas during algorithm training; 47.6 % would feel uncomfortable in the informed consent process for an AI intervention; 10.2 % would no longer trust AI in case of a cyberattack affecting AI support for diagnosis.

Discussion

This survey underscores the importance of AI tools in pediatric oncology that incorporate human oversight in clinical decision-making and training AI algorithms with diverse and representative data. Our findings suggest that pediatric oncologists may not be adequately prepared for the seamless integration of AI in clinical practice.
欧洲儿科肿瘤学家准备将人工智能纳入临床常规
人工智能(AI)在儿科肿瘤学领域前景光明,但其全部潜力面临挑战。我们进行了一项调查,旨在评估欧洲儿科肿瘤学家的观点,深入了解他们对人工智能在临床工作流程中的潜在影响的看法和期望。方法采用人工智能和Shinners人工智能感知(SHAIP)工具,通过四种假设情景进行调查,评估医疗保健专业人员对儿童肿瘤学人工智能的认知。我们采用多项逻辑回归来探讨临床情况的反应与年龄和SHAIP评分的关系。结果获得140份回复,其中108份进行了分析。SHAIP问卷的专业影响平均总分为3.29分(SD 0.93),准备平均总分为2.37分(SD 0.61)。在临床场景方面,34.9 %的受访者在人工智能决策支持与人类诊断不一致的情况下会要求一个确认诊断的程序;55.8% %的人担心在算法训练过程中缺乏某些地理区域数据的情况下,人工智能决策支持系统的泛化性;47.6 %在人工智能干预的知情同意过程中感到不舒服;10.2% 在网络攻击影响人工智能诊断支持的情况下,不再信任人工智能。本调查强调了人工智能工具在儿科肿瘤学中的重要性,这些工具将人类监督纳入临床决策和训练人工智能算法,并具有多样化和代表性的数据。我们的研究结果表明,儿科肿瘤学家可能没有为人工智能在临床实践中的无缝整合做好充分准备。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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