Results 251 to 260 of about 67,030 (311)

Depression, Anxiety and Criminal Behaviour Between Ages 32 and 48: A Propensity Score Matching Analysis From the Cambridge Study in Delinquent Development

Criminal Behaviour and Mental Health, EarlyView.
ABSTRACT Background Depression, anxiety and criminal behaviour are often correlated, but the direction and nature of these associations remain contested. Aims To investigate the temporal relationships between depression and/or anxiety and criminal behaviour at age 32 and depression and/or anxiety and criminal behaviour at age 48.
Kim Reising, Maria M. Ttofi
wiley   +1 more source

Inference for Deep Neural Network Estimators in Generalized Nonparametric Models. [PDF]

J Am Stat Assoc
Meng X, Li Y.
europepmc   +1 more source

Single‐Cell Profiling Reveals Distinct Immune Hallmarks in Untreated Primary Colorectal and Liver Metastasis Cancers

Chronic Diseases and Translational Medicine, EarlyView.
Features the major cell type compositions among colon and liver metastasis. (A) The study design for single‐cell data analysis. (B) The annotated major cell types. Each type was labeled with a special color. (C) Dot plot of canonical marker genes for major cell types. (D) Bar plot of the percentage for each cell type in individuals. (E) Bar plot of the
Zhixun Zhao, Haipeng Chen, Xu Guan, Zheng Jiang, Zheng Liu, Ming Yang, Hengchang Liu, Tianli Chen, Shuangmei Zou, Yibo Gao, Xishan Wang   +10 more
wiley   +1 more source

Application of artificial neural network and general machine learning modelling on CO2 adsorption in moisture equilibrated South African high and medium rank coals

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract This study investigates the effect of moisture on CO2 adsorption in South African coals using both experimental and machine learning approaches. Three coal samples (SL, TN, and EM) with varying ranks (RoVmr: 3.49%, 1.26%, and 0.64%, respectively) were collected from different regions of South Africa.
Kasturie Premlall, Lawrence Koech, Douw Faurie, Khanyisile Lepota   +3 more
wiley   +1 more source

Harnessing machine learning and optimization for informed chemical engineering decisions: A styrene reactor analysis

The Canadian Journal of Chemical Engineering, EarlyView.
This study shows that integrating multiple machine learning models with optimization and decision‐making improves chemical process design, and that a consensus‐based strategy across models provides more robust and reliable operating recommendations than any single model, especially under limited or noisy data conditions.
Farough Agin, Clémence Fauteux‐Lefebvre, Jules Thibault   +2 more
wiley   +1 more source

Evaluating Preclinical-to-Human Bioavailability Classification Using Smooth ROC Curve Estimation. [PDF]

CPT Pharmacometrics Syst Pharmacol
Erdoğan MS.
europepmc   +1 more source

Partial identification with categorical data and nonignorable missing outcomes

Canadian Journal of Statistics, EarlyView.
Abstract Nonignorable missing outcomes are common in real‐world datasets and often require strong parametric assumptions to achieve identification. These assumptions can be implausible or untestable, and so we may wish to forgo them in favour of partially identified models that narrow the set of a priori possible values to an identification region.
Daniel Daly‐Grafstein, Paul Gustafson
wiley   +1 more source

A Sequential Generalized Nonparametric Classification Method for Small-Scale Cognitive Diagnostic Assessment. [PDF]

Behav Sci (Basel)
Li J, Zheng H, Kang C, Cai Y, Tu D.
europepmc   +1 more source

Bayesian inverse ensemble forecasting for COVID‐19

Canadian Journal of Statistics, EarlyView.
Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
wiley   +1 more source

Nonlinear permuted Granger causality

Canadian Journal of Statistics, EarlyView.
Abstract Granger causality is an established, contentious method that seeks causal temporal connections via association and precedence. While not true causal inference, it assists in mapping networks of information flow that may warrant further study.
Noah D. Gade, Jordan Rodu
wiley   +1 more source