无线电技术
计算机科学
医学
医学物理学
重症监护医学
人工智能
作者
Lyndsay N. Harris,Lalitha Shankar,Claire Hildebrandt,Wendy S. Rubinstein,Kristofor K. Langlais,Henry Rodriguez,Adam Berger,John Freymann,Erich P. Huang,P. Mickey Williams,Jean C. Zenklusen,Robert A. Ochs,Živana Težak,Berkman Sahiner
摘要
Abstract The National Institutes of Health–US Food and Drug Administration Joint Leadership Council Next-Generation Sequencing and Radiomics Working Group was formed by the National Institutes of Health–Food and Drug Administration Joint Leadership Council to promote the development and validation of innovative next-generation sequencing tests, radiomic tools, and associated data analysis and interpretation enhanced by artificial intelligence and machine learning technologies. A 2-day workshop was held on September 29-30, 2021, to convene members of the scientific community to discuss how to overcome the “ground truth” gap that has frequently been acknowledged as 1 of the limiting factors impeding high-quality research, development, validation, and regulatory science in these fields. This report provides a summary of the resource gaps identified by the working group and attendees, highlights existing resources and the ways they can potentially be employed to accelerate growth in these fields, and presents opportunities to support next-generation sequencing and radiomic tool development and validation using technologies such as artificial intelligence and machine learning.
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