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multimodal-rp-detection

https://github.com/sotraptis/multimodal-rp-detection

Science Score: 44.0%

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    Low similarity (5.2%) to scientific vocabulary
Last synced: 7 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: sotraptis
  • License: other
  • Language: Python
  • Default Branch: main
  • Size: 66.4 KB
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created 9 months ago · Last pushed 9 months ago
Metadata Files
Readme License Citation

README.md

Multimodal RP Detection – CT Radiomics + Surrogate IR Features

This repository contains code for a feasibility study on early detection of radiation-induced pneumonitis (RP) using a multimodal AI approach and synthetic sample data. The proposed framework combines CT-based radiomics with surrogate features extracted from infrared thermographic data.

Contents

  • Synthetic IR thermal sample (JPG)
  • Simulated CT-based radiomic feature vector (NumPy)
  • Python scripts and Jupyter notebooks for preprocessing, fusion, training, and explainability
  • Visual outputs (ROC curve, metrics, SHAP plot)

Sample Images

Infrared Thermal Sample

Infrared Thermal Sample

CT Radiomics Feature Visualization

CT Radiomics Feature Vector

Requirements

Install all dependencies using: pip install -r requirements.txt

Author

This work was conducted by Sotiris Raptis. Contact: sraptis@uom.edu.gr

Owner

  • Login: sotraptis
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this repository, please cite it as below:"
authors:
  - family-names: Raptis
    given-names: Sotiris
title: "Multimodal RP Detection – CT Radiomics + Surrogate IR Features"
version: 1.0.0
date-released: 2025-07-17

GitHub Events

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Dependencies

requirements.txt pypi
  • joblib *
  • matplotlib *
  • numpy *
  • opencv-python *
  • pandas *
  • pyradiomics *
  • scikit-learn *
  • seaborn *
  • shap *