Results 181 to 190 of about 724,098 (319)

Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs

, 2014
Sebastian Calonico, M. D. Cattaneo, R. Titiunik   +2 more
semanticscholar   +1 more source

Serum Bile Acids Are Useful Indicators of Intrahepatic Recurrence After Initial Curative Hepatectomy for Hepatocellular Carcinoma

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Aim Bile acids accumulation in hepatocytes causes liver damage and contributes to the development of hepatocellular carcinoma. However, the association between serum bile acid levels and postoperative intrahepatic recurrence in hepatocellular carcinoma remains unclear.
Tomoaki Bekki, Masahiro Ohira, Yuki Imaoka, Seiichi Simizu, Tomoyuki Abe, Shintaro Kuroda, Hiroyuki Tahara, Kentaro Ide, Tsuyoshi Kobayashi, Hideki Ohdan   +9 more
wiley   +1 more source

Nonparametric Statistical Methods: Hollander/Nonparametric Statistical Methods

, 1973
M. Hollander, D. Wolfe, E. Chicken
semanticscholar   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Optimal input signal design for closed loop aircraft flutter model analysis. [PDF]

Sci Rep
Jianhong W.
europepmc   +1 more source

A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction

Advanced Intelligent Discovery, EarlyView.
This study develops six machine learning models (k‐nearest neighbors, support vector regression, decision tree, random forest, CatBoost, and backpropagation neural network) to predict SiNx deposition rates in plasma‐enhanced chemical vapor deposition using hybrid production and simulation data.
Yuxuan Zhai, Wenrui Wang, Rui Chen, Tong Yu, Xiaojuan Zheng, Hua Shao, Dashan Shang, Ling Li, Lado Filipovic   +8 more
wiley   +1 more source

The Challenge of Handling Structured Missingness in Integrated Data Sources

Advanced Intelligent Discovery, EarlyView.
As data integration becomes ever more prevalent, a new research question that emerges is how to handle missing values that will inevitably arise in these large‐scale integrated databases? This missingness can be described as structured missingness, encompassing scenarios involving multivariate missingness mechanisms and deterministic, nonrandom ...
James Jackson, Marius Hofert, Eleni‐Rosalina Andrinopoulou, Niels Hagenbuch, Sarah McGough, Chris Harbron, Robin Mitra   +6 more
wiley   +1 more source

Risk functions with outcome measurement error. [PDF]

Biostatistics
Edwards JK, Cole SR, Zivich PN, Ackerman B, Napravnik S, Henderson H, Lash T, Shook-Sa BE.   +7 more
europepmc   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

A Review of R Packages for Bayesian Model-based Clustering of High-dimensional Multivariate Environmental Exposures. [PDF]

Curr Environ Health Rep
Stephenson BJK, Fu Y.
europepmc   +1 more source