Robust deep learning classification of adamantinomatous craniopharyngioma from limited preoperative radiographic images

Robust deep learning classification of adamantinomatous craniopharyngioma from limited preoperative radiographic images

Abstract Deep learning (DL) is a widely applied mathematical modeling technique. Classically, DL models utilize large volumes of training data, which are not available in many healthcare contexts. For patients with brain tumors, non-invasive diagnosis would represent a substantial clinical advance,...

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Auteurs principaux: Eric W. Prince, Ros Whelan, David M. Mirsky, Nicholas Stence, Susan Staulcup, Paul Klimo, Richard C. E. Anderson, Toba N. Niazi, Gerald Grant, Mark Souweidane, James M. Johnston, Eric M. Jackson, David D. Limbrick, Amy Smith, Annie Drapeau, Joshua J. Chern, Lindsay Kilburn, Kevin Ginn, Robert Naftel, Roy Dudley, Elizabeth Tyler-Kabara, George Jallo, Michael H. Handler, Kenneth Jones, Andrew M. Donson, Nicholas K. Foreman, Todd C. Hankinson
Format: article
Langue:EN
Publié: Nature Portfolio 2020
Sujets:
Medicine
R
Science
Q
Accès en ligne:https://doaj.org/article/48a196a679684d488c084efeeb434cda
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https://doaj.org/article/48a196a679684d488c084efeeb434cda

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