Non-invasive prediction of lymph node risk in oral cavity cancer patients using a combination of supervised and unsupervised machine learning algorithms

Autor: Traversoa, A., Hosni-Abdalaty, A., Hasan, M., Tadic, T., Patel, T., Giuliani, M., Kim, J., Ringash, J., Cho, J., Bratman, S., Bayley, A., Waldron, J., O'Sullivan, B., Irish, J., Chepeha, D., De Almeida, J., Goldstein, D., Jaffray, D., Wee, L., Dekker, A., Hope, A., Krol, A, Gimi, BS

Publikováno v: Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging
MEDICAL IMAGING 2020: BIOMEDICAL APPLICATIONS IN MOLECULAR, STRUCTURAL, AND FUNCTIONAL IMAGING

In oral cavity (OC) squamous cell cancer, the incidence of occult nodal metastases varies from 20% to 50% depending and tumor size and thickness. Besides clinical and histopathological factors, image-derived biomarkers may help estimate the probabili

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7aea3958efa59266f2ddf5b3ee90f6c6
https://doi.org/10.1117/12.2560146