嵌合抗原受体
鉴定(生物学)
人工智能
计算机科学
数据集成
数据科学
知识管理
机器学习
医学
T细胞
免疫学
数据挖掘
生物
植物
免疫系统
作者
Fabio Luciani,Arman Safavi,Puneeth Guruprasad,Linhui Chen,Marco Ruella
标识
DOI:10.1158/2643-3230.bcd-23-0240
摘要
Summary: Artificial intelligence could enhance chimeric antigen receptor T-cell therapy outcomes through optimization of all steps, from target identification, vector design, and manufacturing to personalized data-driven clinical decisions. In this report, we highlight steps toward unlocking this potential, including the need for standardized, comprehensive data repositories as a way for addressing barriers to artificial intelligence learning, such as data heterogeneity and patient privacy.
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