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Displaying 1 through 6 of 6 publications.
Romijnders R, Salis F, Hansen C, Kuderle A, Paraschiv-Ionescu A, Cereatti A, Alcock L, Aminian K, Becker C, Bertuletti S, Bonci T, Brown P, Buckley E, Cantu A, Carsin AE, Caruso M, Caulfield B, Chiari L, D'Ascanio I, Del Din S, Eskofier B, Fernstad SJ, Frohlich MS, Garcia Aymerich J, Gazit E, Hausdorff JM, Hiden H, Hume E, Keogh A, Kirk C, Kluge F, Koch S, Mazza C, Megaritis D, Mico-Amigo E, Muller A, Palmerini L, Rochester L, Schwickert L, Scott K, Sharrack B, Singleton D, Soltani A, Ullrich M, Vereijken B, Vogiatzis I, Yarnall A, Schmidt G, Maetzler W. Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases. Front Nuerol. 2023 Oct 16;14:1247532. doi: 10.3389/fneur.2023.1247532
Schwab PE, MacLean E, Chioda M, Moll K, Pasquale M, Mardekian J, Futch T. NSCLC observations combining medical charts and administrative claims data. Poster presented at the 2015 AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; November 5, 2015. Boston, MA. [abstract] Mol Tar Can Ther. 2015 Dec 1; 14(12 S2).