Results 61 to 70 of about 2,267,483 (329)
, 2018 In tensor completion tasks, the traditional low-rank tensor decomposition models suffer from the laborious model selection problem due to their high model sensitivity.
Cao, Jianting +4 more
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Purpose Chemoimmunotherapy with irinotecan, temozolomide, and dinutuximab (I/T/DIN) has emerged as first‐line therapy for relapsed/refractory (r/r) high‐risk neuroblastoma (HRNB) in North America. Topotecan and cyclophosphamide (T/C) are often used in combination with dinutuximab in the setting of lack of response, progression, or incomplete ...
Benjamin J. Lerman +17 more
wiley +1 more source
Optimal Knowledge Component Extracting Model for Knowledge-Concept Graph Completion in Education
IEEE Access, 2023 As people have become accustomed to non-face-to-face education because of the COVID-19 pandemic, adaptive and personalized learning is being emphasized in the field of education.
Hyunhee Choi, Hayun Lee, Minjeong Lee
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Neuropsychological complications may impair the qualitative prognosis of patients with pediatric brain tumors. However, multifaceted evaluations cannot be conducted in all patients because they are time consuming and burdensome for patients.
Ami Tabata +9 more
wiley +1 more source
An Ensemble Matrix Completion Model for Predicting Potential Drugs Against SARS-CoV-2
Frontiers in Microbiology, 2021 Because of the catastrophic outbreak of global coronavirus disease 2019 (COVID-19) and its strong infectivity and possible persistence, computational repurposing of existing approved drugs will be a promising strategy that facilitates rapid clinical ...
Wen Li, Shulin Wang, Junlin Xu
doaj +1 more source
Efficient tensor completion for color image and video recovery: Low-rank tensor train
, 2016 This paper proposes a novel approach to tensor completion, which recovers missing entries of data represented by tensors. The approach is based on the tensor train (TT) rank, which is able to capture hidden information from tensors thanks to its ...
Bengua, Johann A. +3 more
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Patients with high‐risk neuroblastoma who either are refractory to induction chemotherapy or relapse following multi‐modal treatment have a dismal prognosis. Based on data from the BEACON trial, since 2021 the UK national guidelines recommend bevacizumab, irinotecan, and temozolomide (BIT) for patients with relapsed/refractory ...
Thomas J. Jackson +20 more
wiley +1 more source
Nonnegative Tensor Completion via Low-Rank Tucker Decomposition: Model and Algorithm
IEEE Access, 2019 We consider the problem of low-rank tensor decomposition of incomplete tensors that has applications in many data analysis problems, such as recommender systems, signal processing, machine learning, and image inpainting.
Bilian Chen +4 more
doaj +1 more source
Command line completion: an illustration of learning and decision making using the imprecise Dirichlet model [PDF]
, 2003 A method of command line completion based on probabilistic models is described. The method supplements the existing deterministic ones. The probabilistic models are developed within the context of imprecise probabilities.
De Cooman, Gert, Quaeghebeur, Erik
core +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Alveolar soft part sarcoma (ASPS) is a rare soft tissue sarcoma occurring most commonly in adolescence and young adulthood. Methods We present the clinical characteristics, treatments, and outcomes of patients with newly diagnosed ASPS enrolled on the Children's Oncology Group study ARST0332.
Jacquelyn N. Crane +11 more
wiley +1 more source