Results 71 to 80 of about 526,525 (314)
Serial dependence bias can predict the overall estimation error in visual perception. [PDF]
J Vis, 2023 Sun Q +4 more
europepmc +1 more source
AbstractConsider first data-based machine learning techniques. They rely on large sets of examples provided during the training stage and do not learn with equations. Dealing with a situation that do not belong to the training set variability, namely an out-of-distribution sample, can be very challenging for these techniques.
David Ryckelynck +2 more
openaire +1 more source
Least product relative error estimation
Journal of Multivariate Analysis, 2016 A least product relative error criterion is proposed for multiplicative regression models. It is invariant under scale transformation of the outcome and covariates. In addition, the objective function is smooth and convex, resulting in a simple and uniquely defined estimator of the regression parameter.
Chen, Kani +3 more
openaire +4 more sources
Molecular Oncology, EarlyView.Targeted therapy was evaluated in SHH medulloblastoma using neuroepithelial stem cell (NES) and tumor‐derived NES‐like (tNES) models in 2D monolayers and 3D spheroids. PI3K, AKT, and CDK4/6 inhibitors had minimal effects in NES but markedly reduced viability and growth and induced apoptosis in tNES cells, revealing distinct therapeutic vulnerabilities.
Monika Lukoseviciute +4 more
wiley +1 more source
Performance analysis of secrecy rate for SWIPT in massive antenna
Dianxin kexue, 2017 In the multi-drop broadcast system,the existing research is to optimize the single-user security rate in the complete channel state information.In fact,it’s impossible that there exists only one user in the system.The base station often receives ...
Hui BAO +3 more
doaj
Longitudinal Changes in Motor Estimation Error and Motor Function in Patients with Parkinson's Disease: A Case Report. [PDF]
Medicines (Basel), 2023 Sakai K +3 more
europepmc +1 more source
Journal of Computational and Applied Mathematics, 1994 Let \(R[f]\) be the remainder of some linear approximation method (e.g. polynomial or spline approximation, numerical integration or differentiation), having estimates of the form \(| R[f ]|\leq \rho_ i\| f^{(i)} \|_{L^ p[a,b]}\), \(i=m,\dots, r\), for some \(m\) and \(r\) with \(0\leq m\leq r-1\). In many cases, \(\rho_ m\) and \(\rho_ r\), are known,
openaire +2 more sources
Molecular Oncology, EarlyView.We have established a humanized orthotopic patient‐derived xenograft (Hu‐oPDX) mouse model of high‐grade serous ovarian cancer (HGSOC) that recapitulates human tumor–immune interactions. Using combined anti‐PD‐L1/anti‐CD73 immunotherapy, we demonstrate the model's improved biological relevance and enhanced translational value for preclinical ...
Luka Tandaric +10 more
wiley +1 more source
FEBS Open Bio, EarlyView.RoboMic is an automated confocal microscopy pipeline for high‐throughput functional imaging in living cells. Demonstrated with fluorescence recovery after photobleaching (FRAP), it integrates AI‐driven nuclear segmentation, ROI selection, bleaching, and analysis.
Selçuk Yavuz +6 more
wiley +1 more source
Robustness of Adaptive Measurement of Change to Item Parameter Estimation Error. [PDF]
Educ Psychol Meas, 2022 Cooperman AW, Weiss DJ, Wang C.
europepmc +1 more source