相关性(法律)
利益相关者
领域(数学分析)
排名(信息检索)
主题分析
监管科学
透视图(图形)
可靠性(半导体)
知识管理
梅德林
医疗保健
政治学
科学政策
业务
大数据
公司治理
医学研究
公共关系
数据收集
文献计量学
精密医学
作者
Luis Correia Pinheiro,Amanda Langston,Marie Orre,Joerg Zinserling,Konstantina Boumaki,Bastian Hornung,Siobhán O’Sullivan,Gabriel Westman,Karl Broich,Peter R. Arlett
摘要
Regulatory bodies play a central role in providing guidance that enables safe and effective use of artificial intelligence tools in medicine development and evaluation. Regulators can also act as catalysts for regulatory science research. To inform these efforts, a European-wide survey was conducted to solicit stakeholder perspectives on the priority areas for regulatory science research related to the use of artificial intelligence in the medicine lifecycle. Twenty-eight regulatory science research questions were developed covering seven thematic domains: (1) research integrity and intellectual property; (2) accuracy and reliability of AI tools; (3) data governance, confidentiality, and consent; (4) regulation and oversight; (5) ethics, fairness, and bias prevention; (6) resources and support for AI use; and (7) impact on jobs and skills. Within each domain, stakeholders ranked four research challenges. A total of 273 responses were collected from regulators, pharmaceutical industry professionals, patients and consumers, academics, and healthcare professionals. Rankings of research challenges frequently converged across stakeholder groups and levels of AI experience. The top-ranked research questions within each domain were weighted according to the overall importance ranking of each domain to identify a list of 10 priority areas of research. The majority of the 10 priority areas fell within the domains of "Accuracy and reliability of AI tools," "Data governance, confidentiality, and consent," and "Ethics, fairness, and bias prevention." This list aims to support researchers and research funding bodies in addressing knowledge gaps on artificial intelligence in the medicines lifecycle.
科研通智能强力驱动
Strongly Powered by AbleSci AI