A POD-neural-network pipeline estimates six glioblastoma growth parameters from two synthetic tumor snapshots and forecasts tumor volume with 96% accuracy at 150x speedup, but only on synthetic data from a single brain geometry.
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Patient-specific prediction of glioblastoma growth via reduced order modeling and neural networks
A POD-neural-network pipeline estimates six glioblastoma growth parameters from two synthetic tumor snapshots and forecasts tumor volume with 96% accuracy at 150x speedup, but only on synthetic data from a single brain geometry.