Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Marcel Erpenbeck"'
Autor:
Julian Gruendner, Thorsten Schwachhofer, Phillip Sippl, Nicolas Wolf, Marcel Erpenbeck, Christian Gulden, Lorenz A Kapsner, Jakob Zierk, Sebastian Mate, Michael Stürzl, Roland Croner, Hans-Ulrich Prokosch, Dennis Toddenroth
Publikováno v:
PLoS ONE, Vol 14, Iss 11, p e0225442 (2019)
[This corrects the article DOI: 10.1371/journal.pone.0223010.].
Externí odkaz:
https://doaj.org/article/e28cf94954d64abfbeb474e09a131175
Autor:
Julian Gruendner, Thorsten Schwachhofer, Phillip Sippl, Nicolas Wolf, Marcel Erpenbeck, Christian Gulden, Lorenz A Kapsner, Jakob Zierk, Sebastian Mate, Michael Stürzl, Roland Croner, Hans-Ulrich Prokosch, Dennis Toddenroth
Publikováno v:
PLoS ONE, Vol 14, Iss 10, p e0223010 (2019)
BACKGROUND AND OBJECTIVE:To take full advantage of decision support, machine learning, and patient-level prediction models, it is important that models are not only created, but also deployed in a clinical setting. The KETOS platform demonstrated in
Externí odkaz:
https://doaj.org/article/8a7b137fcf1b4cb785d291f76afde964
Autor:
Jan Christoph, Julian Gründner, Hans-Ulrich Prokosch, Philipp Unberath, Christian Maier, Marcel Erpenbeck
Publikováno v:
Applied Clinical Informatics
Background The increasing availability of molecular and clinical data of cancer patients combined with novel machine learning techniques has the potential to enhance clinical decision support, example, for assessing a patient's relapse risk. While th