Reference Manual of MEDiml

Mahdi Ait Lhaj Loutfi, Simon Provost, Élodie Gillard, Moustafa Amine Bezzahi, Alexander Chum +11

Radiomics is the high-throughput extraction of quantitative features (e.g., tumor shape, intensity distributions, and texture) from medical images to characterize tissues and uncover disease patterns invisible to the human eye. These features can serve as candidate imaging biomarkers for cancer diagnosis, prognosis, and classification. However, extracting thousands of features makes it difficult to identify the most informative ones for a given clinical task, while implementing an end-to-end workflow can require programming expertise that limits accessibility for clinical researchers. Hence, we propose MEDiml, an open-source, standards-compliant radiomics platform connecting feature extraction, predictive modeling, and interpretation through complementary graphical and programmatic interfaces. MEDiml combines a Python package (MEDiml-pkg) with a graphical desktop application (MEDiml-app) that enables researchers to conduct experiments without writing code. Both interfaces use the same computational implementation, and code generation exports graphically configured workflows as executable Python code, facilitating reproducibility and collaboration between clinical researchers and…