Article

Predicting tumour evolution and drug resistance from heterogenous longitudinal cancer data

2024-12-30

Abstract excerpt

The kinetic parameters of cancer population dynamics are critical for developing reliable predictors of tumour growth patterns, extracting metrics for patient stratification and creating algorithms that can forecast clinically significant events. Here, we introduce a model-based Bayesian framework that leverages longitudinal phenotypic (e.g., tumour volume, cell counts) or genotypic (e.g., mutation frequency) data...

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Identifiers and source

Literature Corpus work: 54804845-529e-5dd7-a093-61d201b7ee4a
DOI: 10.1101/2024.12.30.630757

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