Results 91 to 100 of about 2,787,150 (169)

A robust and efficient change point detection method for high-dimensional linear models. [PDF]

J Appl Stat
Han ZC, Zhang KS, Zhao YY.
europepmc   +1 more source

Detecting Structural Change Point in ARMA Models via Neural Network Regression and LSCUSUM Methods. [PDF]

Entropy (Basel), 2023
Ri XH, Chen Z, Liang Y.
europepmc   +1 more source

Detection of circulating tumor DNA in colorectal cancer patients using a methylation‐specific droplet digital PCR multiplex

Molecular Oncology, EarlyView.
We developed a cost‐effective methylation‐specific droplet digital PCR multiplex assay containing tissue‐conserved and tumor‐specific methylation markers. The assay can detect circulating tumor DNA with high accuracy in patients with localized and metastatic colorectal cancer.
Luisa Matos do Canto, Louise Raunkilde, Jan Lindebjerg, Mads Malik Aagaard, Christina Therkildsen, Jakob Kleif, Lars Henrik Jensen, Torben Frøstrup Hansen, Rikke Fredslund Andersen   +8 more
wiley   +1 more source

Noise-Adaptive State Estimators with Change-Point Detection. [PDF]

Sensors (Basel)
Hou X, Zhao S, Hu J, Lan H.
europepmc   +1 more source

Forecasting and change point test for nonlinear heteroscedastic time series based on support vector regression. [PDF]

PLoS One, 2022
Wang H, Guo M, Lee S, Chua CH.
europepmc   +1 more source

Transcriptional network analysis of PTEN‐protein‐deficient prostate tumors reveals robust stromal reprogramming and signs of senescent paracrine communication

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, Jose I. Lopez, Aitziber Ugalde‐Olano, Maite Zufiaurre, Ianire Astobiza, Natalia Martin‐Martin, Laura Bozal‐Basterra, Saioa Garcia‐Longarte, Amaia Zabala‐Letona, Sofia Rey, Aida Santos‐Martin, Miguel Unda, Ana Loizaga‐Iriarte, Mariona Graupera, Paolo Nuciforo, Arkaitz Carracedo, Isabel Mendizabal   +16 more
wiley   +1 more source

Change-point detection of the Kumaraswamy skew-t distribution based on modified information criterion. [PDF]

J Appl Stat
Wang J, Ning W.
europepmc   +1 more source

The CUSUM statistic of change point under NA sequences. [PDF]

Appl Math, 2021
Ling J, Li XQ, Yang WZ, Jiao JL.
europepmc   +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, Clara Frick, Ben Schöttker, Bernd Holleczek, Hermann Brenner   +4 more
wiley   +1 more source

Iterative smoothing for change-point regression function estimation. [PDF]

J Appl Stat
Thompson JRJ.
europepmc   +1 more source