AI-based augmentation of oncology clinical trials
Oncology clinical trials are often characterized by slow accrual, high failure rates and limited generalizability, reflecting both biological complexity and operational inefficiencies. Advances in artificial intelligence (AI) - enabled by large-scale electronic health record datasets and machine learning methods - offer new opportunities to address these challenges across the clinical trial lifecycle. In this Review, we discuss applications of AI across pre-trial design, trial conduct, and post-trial inference a…

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