MR

2021 | AMINN: Autoencoder-Based Multiple Instance Neural Network Improves Outcome Prediction in Multifocal Liver Metastases

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

Short Description: We built a multiple instance learning network with radiomic features of liver MRI to predict survival of multifocal colorectal cancer liver metastases patients. We empirically validated our hypothesis that incorporating imaging features of all lesions improves outcome prediction for multifocal cancer. We released our code at https://github.com/martellab-sri/AMINN.
Modality: MR
Organ: Liver
Disease: Cancer

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150 150 MaLMIC - Machine Learning in Medical Imaging Consortium