Risk Classification of Brain Metastases via Radiomics, Delta-Radiomics and Machine Learning

no code implementations • 17 Feb 2023 • Philipp Sommer, Yixing Huang, Christoph Bert, Andreas Maier, Manuel Schmidt, Arnd Dörfler, Rainer Fietkau, Florian Putz

We hypothesized that using radiomics and machine learning (ML), metastases at high risk for subsequent progression could be identified during follow-up prior to the onset of significant tumor growth, enabling personalized follow-up intervals and early selection for salvage treatment.

Continual Learning for Peer-to-Peer Federated Learning: A Study on Automated Brain Metastasis Identification

no code implementations • 26 Apr 2022 • Yixing Huang, Christoph Bert, Stefan Fischer, Manuel Schmidt, Arnd Dörfler, Andreas Maier, Rainer Fietkau, Florian Putz

With iterative continual learning (i. e., the shared model revisits each center multiple times during training), the sensitivity is further improved to 0. 914, which is identical to the sensitivity using mixed data for training.

Continual Learning Federated Learning