Results 131 to 140 of about 439,420 (307)

Model-Robust Interval Estimation

, 2003
Confidence intervals are one of the most useful statistical tools. This dissertation is a study of several methods for forming confidence intervals that are insensitive to model assumptions, provided that the mean model for the data is not misspecified.
Gotwalt, Christopher Michael
core  

Patient therapy outcome modeling in cancer organoids is improved by cancer‐associated fibroblasts and organoid assembly convolution

Molecular Oncology, EarlyView.
Patient‐derived organoids (PDOs) from pancreatic, colorectal, and gastric cancers were used to evaluate standard and experimental therapies. Incorporating cancer‐associated fibroblasts (CAFs) into organoid cultures improved patient therapy outcome prediction.
Marcin Grochowski, Liudmyla Dolinchuk, Michał Jerzak, Albert Gandurski, Tomasz Grochowski, Weronika Wojtyś, Maciej Zadrożny, Wojciech Kaźmierczak, Małgorzata Lenarcik, Marta Matejak‐Górska, Radosław Samsel, Tomasz Olesiński, Dawid Walerych   +12 more
wiley   +1 more source

Robust MM-Estimation and Inference in Mixed Linear Models [PDF]

Mixed linear models are used to analyse data in many settings. These models generally rely on the normality assumption and are often fitted by means of the maximum likelihood estimator (MLE) or the restricted maximum likelihood estimator (REML). However,
Stephane Heritier, Samuel Copt
core  

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

S-estimation and a robust conditional Akaike information criterion for linear mixed models. [PDF]

We study estimation and model selection on both the fixed and the random effects in the setting of linear mixed models using outlier robust S-estimators.
Tharmaratnam, Kukatharmini, Claeskens, Gerda   +1 more
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

Robust canonical correlations: a comparative study. [PDF]

Several approaches for robust canonical correlation analysis will be presented and discussed. A first method is based on the definition of canonical correlation analysis as looking for linear combinations of two sets of variables having maximal (robust ...
Croux, Christophe, Filzmoser, P, Oliveira, R, Branco, J   +3 more
core  

Optimizing precision farming: enhancing machine learning efficiency with robust regression techniques in high-dimensional data

Journal of Nigerian Society of Physical Sciences
Smart precision farming leverages IoT, cloud computing, and big data to optimize agricultural productivity, lower costs, and promote sustainability through digitalization and intelligent methodologies.
Nour Hamad Abu Afouna, Majid Khan Majahar Ali   +1 more
doaj   +1 more source

Analysing the significance of small conformational changes and low occupancy states in serial crystallographic data

FEBS Open Bio, EarlyView.
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill, Yelyzaveta Pulnova, Elke De Zitter, Helen M. Ginn, Briony A. Yorke   +4 more
wiley   +1 more source

Monte Carlo Techniques in Studying Robust Estimators [PDF]

Recent work on robust estimation has led to many procedures, which are easy to formulate and straightforward to program but difficult to study analytically.
David C. Hoaglin
core