Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Meiyan Xie"'
Publikováno v:
Food Weekly News; 6/27/2024, p20-20, 1p
Publikováno v:
Actas Espanolas de Psiquiatria. 2024, Vol. 52 Issue 3, p248-255. 8p.
Publikováno v:
Journal of Research in Medical Sciences, Vol 20, Iss 2, Pp 185-195 (2015)
Sepsis is a systemic inflammatory response to infection. Sepsis, which can lead to severe sepsis, septic shock, and multiple organ dysfunction syndrome, is an important cause of mortality. Pathogenesis is extremely complex. In recent years, cell hypo
Externí odkaz:
https://doaj.org/article/39c2edde12e7402b8dddd8f551c96397
Publikováno v:
BIBM
Prediction of cancer survival time is of considerable interest in medicine as it leads to better patient care and reduces health care costs. In this study, we propose a multi-path multimodal neural network that predicts Glioblastoma Multiforme (GBM)
Autor:
Yunzhi Li, Yunzhe Xue, Saum Rahimi, Lauren A. Huntress, Usman Roshan, William E. Beckerman, Meiyan Xie, Justin Ady
Publikováno v:
BIBM
Carotid ultrasound is a screening modality used by physicians to direct treatment in the prevention of ischemic stroke in high-risk patients. It is a time intensive process that requires highly trained technicians and physicians. Evaluation of a caro
Publikováno v:
ICMLA
Motivated by the general robustness properties of the 01 loss we propose a single hidden layer 01 loss neural network trained with stochastic coordinate descent as a defense against adversarial attacks in machine learning. One measure of a model's ro
Autor:
William E. Beckerman, Justin Ady, Meiyan Xie, Yunzhu Li, Saum Rahimi, Usman Roshan, Lauren A. Huntress, Yunzhe Xue
Publikováno v:
ICMLA
Carotid ultrasound is a screening modality used by physicians to direct treatment in the prevention of ischemic stroke in high-risk patients. It is a time intensive process that requires highly trained technicians and physicians. Evaluation of a caro
Publikováno v:
ICMLA
The 01 loss gives different and more accurate boundaries than convex loss models in the presence of outliers. Could the difference of boundaries translate to adversarial examples that are non-transferable between 01 loss and convex models? We explore
Autor:
Anna M. Barrett, Yunzhe Xue, Usman Roshan, Fadi G. Farhat, Jeffrey R. Binder, William W. Graves, Olga Boukrina, Meiyan Xie
Publikováno v:
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries ISBN: 9783030466428
BrainLes@MICCAI (2)
BrainLes@MICCAI (2)
The identification of brain tumor type, shape, and size from MRI images plays an important role in glioma diagnosis and treatment. Manually identifying the tumor is time expensive and prone to error. And while information from different image modalit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::afbaaac2b3304ef2ba0a8c5781d1e3cc
https://doi.org/10.1007/978-3-030-46643-5_25
https://doi.org/10.1007/978-3-030-46643-5_25
Publikováno v:
ICMLA
The 01 loss while hard to optimize is least sensitive to outliers compared to its continuous differentiable counterparts, namely hinge and logistic loss. Recently the 01 loss has been shown to be most robust compared to surrogate losses against corru