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Projekt | Miracle2

Laufzeit:

A Machine learning approach to Identify patients with Resected non-small-cell lung cAnCer with high risk of reLapsE

Forschungsthemen

Anwendungsfelder

MIRACLE comprises a consortium of academics and industry partners to understand how machine learning can be utilised to predict the risk of relapse for patients with resected non-small cell lung cancer. The project includes six work packages, this contract focusing on “WP5: Development of the Machine Learning Model”. WP5 requires DFKI to build a bespoke machine learning model for predicting risk of NSCLC relapse – in particular this should include identifying and testing the potential of deep learning survival models.

Partner

Universität Leipzig

Projekt teilen auf:

Kontakt

Prof. Dr. Sebastian Vollmer Prof. Dr. Sebastian Vollmer

Keyfacts

Publikationen

  1. MiracleNet: A biologically-interpretable machine learning model for resected non-small-cell lung cancer​

    Rashika Jakhmola; David Antony Selby; Mert Cihan; Dusan Prascevic; Elisabetta Petracci; Paola Ulivi; Enriqueta Felip; Rocío Caro Consuegra; Franco Stella; Piergiorgio Solli; Desideria Argnani; Milena Urbini; Johannes Urban Mayer; Sebastian Vollmer; Christian Martin; Jan Ewald; Maximilian Sprang

    In: Computational and Structural Biotechnology Journal, Vol. 0145, No. ja, Pages 1-26, American Association for the Advancement of Science, 6/2026.

Fördergeber

Universität Leipzig

00693645