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swin

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This repository presents a radiodosiomics framework for personalized [¹⁷⁷Lu]Lu-PSMA-617 RLT in mCRPC. It includes feature selection and ML models using clinical, radiomic, and dosiomic features, plus nnU-Net and Swin UNETR DL models with SSL to predict Monte Carlo–based dose rate maps.

  • Updated Sep 28, 2025
  • Jupyter Notebook

The initial stage of this work focuses on creating a segmented image from a given satellite image with different classes. In the second stage, these images should be converted to an ABM-friendly format. At the final stage, they can be used to simulate the real-world environment with related agents using a suitable Agent-based model.

  • Updated Feb 14, 2024
  • Jupyter Notebook

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