HAL (France)
open access
SHERLOC: An interpretable deep learning model for longitudinal circulating tumor DNA data in survival analysis
Longitudinal circulating tumor DNA (ctDNA) measurements offer a noninvasive means to monitor treatment response, but clinical trial data present substantial methodological challenges due to high-dimensional short longitudinal ctDNA sequences and limited sample sizes. We introduce SHERLOC, a deep lea
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