Artificial intelligence in paediatric cancer: Insights from innovation experts in the UNICA4EU project

Pilar Gangas , Norbert Graf , Shuping Wen , Carlotta Cattaneo , Marilena Bicchieri , Niamh Lennox-Chhugani
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Abstract

This article presents the results of interviews with AI development and innovation experts, focusing on the potential contribution of AI to paediatric cancer treatment, its barriers and facilitators. AI-based technologies are expanding in health care provision and potentially to paediatric oncology, particular imageology. However, no AI based technology specifically developed for paediatric cancer has been identified. Interviews identified key barriers, including legal, regulatory and ethical challenges; validation and evaluation standards; integration with public healthcare systems; acceptance, explainability and trust of AI technologies; digital literacy and skills development; data management and privacy Protection; and promoting multidisciplinary collaboration. Facilitators largely coincide, including legal, regulatory and ethical considerations; data management and storage; building trust and ensuring privacy; engaging key stakeholders; promoting multidisciplinary collaboration through AI technologies; and education, training and innovation programmes. Barriers can be turned into facilitators if properly managed. These interviews were conducted under the EU funded project UNICA4EU (Towards a UNIque approach for artificial intelligence data-driven solutions to fight Childhood cAncer FOR EUrope)(1), which was implemented between 2022 and 2024. The goal of the overall project was to analyse the current landscape of Artificial Intelligence (AI) and to map applications to Childhood Cancer. This work further develops and confirms the results of a previous EU-funded pilot project, A crowdsourced ecosystem to fight childhood cancer (EU4CHILD)(1).
儿童癌症中的人工智能:来自UNICA4EU项目创新专家的见解
本文介绍了对人工智能发展和创新专家的访谈结果,重点讨论了人工智能对儿科癌症治疗的潜在贡献、其障碍和促进因素。基于人工智能的技术正在扩大卫生保健服务,并可能扩展到儿科肿瘤学,特别是影像学。然而,目前还没有发现专门针对儿科癌症开发的基于人工智能的技术。访谈确定了主要障碍,包括法律、监管和道德挑战;验证和评价标准;与公共卫生系统整合;人工智能技术的接受度、可解释性和信任度;数字素养和技能发展;数据管理和隐私保护;促进多学科合作。促成因素基本上是一致的,包括法律、监管和道德方面的考虑;数据管理和存储;建立信任和确保隐私;吸引关键利益相关者;通过人工智能技术促进多学科合作;以及教育、培训和创新项目。如果管理得当,障碍可以变成促进因素。这些访谈是在欧盟资助的UNICA4EU项目(为欧洲抗击儿童癌症的人工智能数据驱动解决方案的独特方法)(1)下进行的,该项目于2022年至2024年间实施。整个项目的目标是分析人工智能(AI)的现状,并将其应用于儿童癌症。这项工作进一步发展并证实了之前欧盟资助的试点项目——对抗儿童癌症的众包生态系统(EU4CHILD)(1)的结果。
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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