Results 141 to 150 of about 1,524,562 (340)

Robust estimation of dimension reduction space [PDF]

Most dimension reduction methods based on nonparametric smoothing are highly sensitive to outliers and to data coming from heavy-tailed distributions. We show that the recently proposed methods by Xia et al.
Pavel Cizek, Wolfgang Härdle
core  

Robust estimation of mixing measures in finite mixture models [PDF]

, 2017
Nhat Ho, XuanLong Nguyen, Ya’acov Ritov   +2 more
openalex   +1 more source

Clinical performance of the urine‐based TERT promoter AbsoluteQ Digital PCR for non‐invasive detection of bladder cancer

Molecular Oncology, EarlyView.
A urine‐based digital PCR assay targeting two hotspot TERT promoter variants detected bladder cancer with high sensitivity and no false positives in this case–control cohort. The streamlined AbsoluteQ workflow outperformed Sanger sequencing and supports non‐invasive molecular testing for bladder cancer detection.
Anna Nykel, Izabela Kubiak, Lena Rutkowska, Żaneta Kasprzyk, Łukasz Kępczyński, Michał Bednarek, Dariusz Sobieraj, Jacek Wilkosz, Piotr Kania, Adam Jędrzejczyk, Bogdan Kałużewski, Agnieszka Gach, Tadeusz Kałużewski   +12 more
wiley   +1 more source

Information-Theoretic Disturbance Minimization for Unified Secure or Robust Distributed Estimation in Presence of Impulsive FDI Attack or Impulsive Noise

IEEE Access
In this paper, an information-theoretic and statistical viewpoint of distributed estimation problem is considered as the contribution of the work. So, a novel minimum information-theoretic disturbance diffusion least-mean-square (LMS) algorithm is ...
Hadi Zayyani, Mohammad Salman, Mostafa Rashdan, Hasan Abuhilal   +3 more
doaj   +1 more source

Robust adaptive quantum phase estimation

New Journal of Physics, 2015
Quantum parameter estimation is central to many fields such as quantum computation, communications and metrology. Optimal estimation theory has been instrumental in achieving the best accuracy in quantum parameter estimation, which is possible when we ...
Shibdas Roy, Ian R Petersen, Elanor H Huntington   +2 more
doaj   +1 more source

Automated FRAP microscopy for high‐throughput analysis of protein dynamics in chromatin organization and transcription

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, Bart Geverts, Johan A. Slotman, Andrea Sacchetti, Stefan Prekovic, Martin E. van Royen, Adriaan B. Houtsmuller   +6 more
wiley   +1 more source

A Robust Recursive State Estimation Method for Uncertain Linear Discrete-Time Systems

Automation
This study presents a robust estimation approach for linear discrete-time systems subject to parametric uncertainties. To address model mismatch, the proposed method enhances the MHE framework, thereby improving estimation accuracy.
Jiehui Gao, Huabo Liu
doaj   +1 more source

Differential regulation of ZFAS1 splice variants by endoplasmic reticulum stress in hepatocyte cell lines

FEBS Open Bio, EarlyView.
ZFAS1 is a lncRNA promoting cell proliferation and migration, exhibiting high expression in various cancers. It is conserved, widely expressed, and produces multiple splice variants with unclear roles. We identified several splice variants in hepatocyte models, and found that inhibiting or suppressing regulators of the unfolded protein response (PERK ...
Sébastien Soubeyrand, Paulina Lau, Ruth McPherson   +2 more
wiley   +1 more source

Robust estimation of the vector autoregressive model by a trimmed least squares procedure. [PDF]

The vector autoregressive model is very popular for modeling multiple time series. Estimation of its parameters is done by a least squares procedure. However, this estimation method is unreliable when outliers are present in the data, and there is a need
Croux, Christophe, Joossens, Kristel
core  

Applicability of mitotic figure counting by deep learning: a development and pan‐cancer validation study

FEBS Open Bio, EarlyView.
In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes, Maria X. Isaksen, Frida Julbø, Manohar Pradhan, Andreas Kleppe, Sepp De Raedt, Ole‐Johan Skrede, Turid Torheim, John Arne Nesheim, Hans Martin Mohn, Hanne A. Askautrud, Karolina Cyll, Wanja Kildal, Emma Rewcastle, Melinda Lillesand, Vebjørn Kvikstad, Emiel Janssen, Robert Jones, Odd Terje Brustugun, Bjørn Brennhovd, Erik Skaaheim Haug, Lill‐Tove Rasmussen Busund, Elin Richardsen, Sigve Andersen, Tom Dønnem, Kristina Lindemann, Gunnar Kristensen, Neil A. Shepherd, Marco Novelli, Knut Liestøl, David Kerr, Håvard E. Danielsen, Tarjei S. Hveem   +32 more
wiley   +1 more source