数字化病理学
工作流程
心灵感应学
协调
可交付成果
互操作性
计算机科学
病理
医学物理学
医学
数据科学
人工智能
系统工程
工程类
医疗保健
远程医疗
数据库
经济增长
操作系统
物理
经济
声学
作者
Gabriele Pohlmeyer-Esch,Charles Halsey,Julie Boisclair,Sripad Ram,Sarah Kitz,Brian L. Knight,Pierre Moulin,Anna-Lena Frisk
标识
DOI:10.1177/01926233251340622
摘要
Advancements in digital pathology and artificial intelligence (AI) have enormous transformative potential for nonclinical toxicologic pathology and are already changing the ways in which pathologists work. However, due to the rapid evolution of digital pathology and AI, the toxicologic pathology community would benefit from an update on these advancements, which can be used to aid drug development. Here we identify key articles published on the use of digital pathology and AI in the field and provide current regulatory statuses and guidelines. For digital pathology, we outline the requirements for equipment, validation processes, workflows, and archiving. Challenges to achieve system interoperability and to establish harmonization through Digital Imaging and Communications in Medicine compatibility are also discussed. For AI, we highlight considerations for model development, including the determination of ground truth, problems that may arise due to bias, and how the accuracy and precision of AI algorithms can be assessed. Finally, we discuss the challenges and potential for AI-assisted toxicologic pathology, picturing a future where technology and scientific expertise work hand-in-hand to improve the quality and efficiency of nonclinical drug safety evaluation. This publication is a deliverable of the European Innovative Medicines Initiative 2 Joint Undertaking, “Bigpicture.”
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