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  • Eposter self-study
  • PS01.17

Machine learning-based survival prediction for newly diagnosed glioma patients using radiomic features extracted from MRI and PET images

Dr. Lena Kaiser
Munich / DE

Appointment

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Poster (self-study) 1

Poster

Machine learning-based survival prediction for newly diagnosed glioma patients using radiomic features extracted from MRI and PET images

Session

Artificial intelligence (self-study)

Topics

  • Artificial intelligence
  • Diagnostic and therapeutic nuclear medicine

Authors

Dr. Lena Kaiser (Munich / DE), Stefanie Quach (Munich / DE), Adrian Jun Zounek (Munich / DE), Artem Zatcepin (Munich / DE), Adrien Holzgreve (Munich / DE), Sabrina Kirchleitner (Munich / DE), Viktoria C. Ruf (Munich / DE), Prof. Dr. Matthias Brendel (Munich / DE), Niklas Thon (Munich / DE), Jochen Herms (Munich / DE), Markus Riemenschneider (Regensburg / DE), Sophia Stöcklein (Munich / DE), Maximilian Niyazi (Munich / DE), Rainer Rupprecht (Munich / DE), Jörg-Christian Tonn (Munich / DE), Prof. Dr. Peter Bartenstein (Munich / DE), Prof. Dr. Sibylle I. Ziegler (Munich / DE), Louisa von Baumgarten (Munich / DE), Nathalie Lisa Albert (Munich / DE)

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