Results 101 to 110 of about 1,076,580 (347)

Control of Confounding and Reporting of Results in Causal Inference Studies. Guidance for Authors from Editors of Respiratory, Sleep, and Critical Care Journals

Annals of the American Thoracic Society, 2019
Control of Confounding and Reporting of Results in Causal Inference Studies Guidance for Authors fromEditors of Respiratory, Sleep, andCritical Care Journals David J. Lederer*, Scott C. Bell*, Richard D. Branson*, James D.
D. Lederer, S. Bell, R. Branson, J. Chalmers, R. Marshall, D. Maslove, D. Ost, N. Punjabi, M. Schatz, A. Smyth, P. Stewart, S. Suissa, A. Adjei, C. Akdis, É. Azoulay, J. Bakker, Z. Ballas, P. Bardin, E. Barreiro, R. Bellomo, J. Bernstein, V. Brusasco, T. Buchman, S. Chokroverty, N. Collop, J. Crapo, D. Fitzgerald, L. Hale, N. Hart, F. Herth, T. Iwashyna, G. Jenkins, M. Kolb, G. Marks, P. Mazzone, R. Moorman, T. Murphy, T. Noah, Paul R Reynolds, D. Riemann, R. Russell, A. Sheikh, G. Sotgiu, E. Swenson, R. Szczesniak, R. Szymusiak, J. Teboul, J. Vincent   +47 more
semanticscholar   +1 more source

LDAcoop: Integrating non‐linear population dynamics into the analysis of clonogenic growth in vitro

Molecular Oncology, EarlyView.
Limiting dilution assays (LDAs) quantify clonogenic growth by seeding serial dilutions of cells and scoring wells for colony formation. The fraction of negative wells is plotted against cells seeded and analyzed using the non‐linear modeling of LDAcoop.
Nikko Brix, Daniel Samaga, Katharina Gehr, Benedek Dankó, Mohamed Schumann, Guido Drexler, Ahmed Alnatsha, Georg Beyer, Ujjwal Mahajan, Martin Selmansberger, Julia Mayerle, Claus Belka, Horst Zitzelsberger, Kirsten Lauber   +13 more
wiley   +1 more source

Invariant Causal Prediction for Nonlinear Models

Journal of Causal Inference, 2018
An important problem in many domains is to predict how a system will respond to interventions. This task is inherently linked to estimating the system’s underlying causal structure.
Heinze-Deml Christina, Peters Jonas, Meinshausen Nicolai   +2 more
doaj   +1 more source

Collaborative causal inference with a distributed data-sharing management [PDF]

, 2022
Mengtong Hu, Xu Shi, Peter X. -K. Song
openalex   +1 more source

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects

Molecular Oncology, EarlyView.
To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley   +1 more source

From urn models to box models: Making Neyman's (1923) insights accessible

Journal of Causal Inference
Neyman’s 1923 paper introduced the potential outcomes framework and the foundations of randomization-based inference. We discuss the influence of Neyman’s paper on four introductory to intermediate-level textbooks by Berkeley faculty members (Scheffé ...
Lin Winston, Dudoit Sandrine, Nolan Deborah, Speed Terence P.   +3 more
doaj   +1 more source

Approximate Kernel-Based Conditional Independence Tests for Fast Non-Parametric Causal Discovery

Journal of Causal Inference, 2019
Constraint-based causal discovery (CCD) algorithms require fast and accurate conditional independence (CI) testing. The Kernel Conditional Independence Test (KCIT) is currently one of the most popular CI tests in the non-parametric setting, but many ...
Strobl Eric V., Zhang Kun, Visweswaran Shyam   +2 more
doaj   +1 more source

A review of causal inference in forensic medicine [PDF]

, 2020
Putri Dianita Ika Meilia, Michael Freeman, Herkutanto, Maurice P. Zeegers   +3 more
openalex   +1 more source

Targeted modulation of IGFL2‐AS1 reveals its translational potential in cervical adenocarcinoma

Molecular Oncology, EarlyView.
Cervical adenocarcinoma patients face worse outcomes than squamous cell carcinoma counterparts despite similar treatment. The identification of IGFL2‐AS1's differential expression provides a molecular basis for distinguishing these histotypes, paving the way for personalized therapies and improved survival in vulnerable populations globally.
Ricardo Cesar Cintra, Lucca Paolo Hsu Helmich, Daniel Rodrigues de Bastos, Laura Sichero, Patrícia Savio de Araujo‐Souza, Fabio Passetti, Luisa Lina Villa   +6 more
wiley   +1 more source

Conditional generative adversarial networks for individualized causal mediation analysis

Journal of Causal Inference
Most classical methods popularly used in causal mediation analysis can only estimate the average causal effects and are difficult to apply to precision medicine.
Huan Cheng, Sun Rongqian, Song Xinyuan
doaj   +1 more source