Results 91 to 100 of about 4,733,796 (328)
A Novel Online and Non-Parametric Approach for Drift Detection in Big Data
IEEE Access, 2017 A sizable amount of current literature on online drift detection tools thrive on unrealistic parametric strictures such as normality or on non-parametric methods whose power performance is questionable.
Moinak Bhaduri +3 more
doaj +1 more source
Non parametric methods of disparity computation
International Journal of Engineering & Technology, 2018 Disparity is inversely proportional to depth. Informationabout depth is a key factor in many real time applicationslikecomputer vision applications, medical diagnosis, model precision etc. Disparity is measured first in order to calculate the depth that suitsthe real world applications. There are two approaches viz., active and passive methods.
Priya Charles, A V.Patil
openaire +2 more sources
, 2017 In the present explorative study, different time-series analysis methods, such as moving average, deterministic methods (linear trend with seasonality), and non-parametric Mann–Kendall trend test, were applied to monthly precipitation data from January ...
T. Kocsis, I. Kovács-Székely, A. Anda
semanticscholar +1 more source
Molecular Oncology, EarlyView.Combining PTEN protein assessment and transcriptomic profiling of prostate tumors, we uncovered a network enriched in senescence and extracellular matrix (ECM) programs associated with PTEN loss and conserved in a mouse model. We show that PTEN‐deficient cells trigger paracrine remodeling of the surrounding stroma and this information could help ...
Ivana Rondon‐Lorefice +16 more
wiley +1 more source
ESTIMATING NON-PARAMETRIC AND PARAMETRIC TRANSFORMATION FUNCTIONS FROM SURVEY DATA: AN APPLICATION OF MINIMUM CROSS-ENTROPY [PDF]
A model of a (convex) technology of representative and non-representative firms in a heterogeneous sector is presented in non-parametric and parametric versions. The heterogeneity is specified with error terms.
Hoveid, Oyvind
core +1 more source
Next‐generation proteomics improves lung cancer risk prediction
Molecular Oncology, EarlyView.This is one of very few studies that used prediagnostic blood samples from participants of two large population‐based cohorts. We identified, evaluated, and validated an innovative protein marker model that outperformed an established risk prediction model and criteria employed by low‐dose computed tomography in lung cancer screening trials.
Megha Bhardwaj +4 more
wiley +1 more source
The Kernel Estimation in Biosystems Engineering [PDF]
Journal of Systemics, Cybernetics and Informatics, 2008 In many fields of biosystems engineering, it is common to find works in which statistical information is analysed that violates the basic hypotheses necessary for the conventional forecasting methods.
Esperanza Ayuga Téllez +4 more
doaj
When are Non-Parametric Methods Robust?
, 2020 accepted to ICML ...
Bhattacharjee, Robi, Chaudhuri, Kamalika
openaire +2 more sources
Effective therapeutic targeting of CTNNB1‐mutant hepatoblastoma with WNTinib
Molecular Oncology, EarlyView.WNTinib, a Wnt/CTNNB1 inhibitor, was tested in hepatoblastoma (HB) experimental models. It delayed tumor growth and improved survival in CTNNB1‐mutant in vivo models. In organoids, WNTinib outperformed cisplatin and showed enhanced efficacy in combination therapy, supporting its potential as a targeted treatment for CTNNB1‐mutated HB.
Ugne Balaseviciute +17 more
wiley +1 more source
An innovative approach based on real-world big data mining for calculating the sample size of the reference interval established using transformed parametric and non-parametric methods. [PDF]
BMC Med Res Methodol, 2022 Ma C +8 more
europepmc +1 more source