Results 181 to 190 of about 29,456 (261)

Evaluating Vaginal Microbiome Effects on Antiretroviral Exposure in the Female Genital Tract Using Pharmacometric and Machine Learning Approaches

Clinical Pharmacology &Therapeutics, EarlyView.
Antiretroviral pre‐exposure prophylaxis (PrEP) is less effective in women than expected, partly because drug exposure within the female genital tract is variable and may be influenced by the vaginal microbiome. We developed an integrated pharmacometrics and machine learning framework to evaluate associations between vaginal microbiome composition and ...
Diqin Yan, Lindsey B. Collins, Christopher Staley, Flavia Kiweewa Matovu, Pamala Jacobson, Melanie Nicol, Shen Cheng   +6 more
wiley   +1 more source

Machine Learning Prediction of Anterior Open-Bite Development After Stabilization Splint Treatment in Temporomandibular Disorder. [PDF]

Clin Exp Dent Res
Hwang JJ, Jeon HM, Ju HM, Jeong SH, Ahn YW, Ok SM.   +5 more
europepmc   +1 more source

Efficiency and Perceptions in Public CSR: An Integrated Efficiency–Perception Analysis of Spanish Defence Delegations

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Public organisations often experience a discrepancy between improvements in technical efficiency and stakeholders' perceptions of integrity and performance. This study analyses the mechanisms that may underlie this efficiency–perception discrepancy in Spanish Defence Delegations during 2020–2023.
José Solana‐Ibáñez, Manuel Caravaca‐Garratón   +1 more
wiley   +1 more source

Old data, new tricks: Comprehensive computational analysis of 10 years of multi‐center EuroFlow acute myeloid leukemia diagnostic immunophenotypic data

Cytometry Part B: Clinical Cytometry, EarlyView.
Abstract Acute myeloid leukemia (AML) is characterized by high genotypic and immunophenotypic heterogeneity. We collected an extensive dataset containing 5366 flow cytometry files from 885 AML patients, stained with the EuroFlow acute leukemia orientation tube (ALOT) and AML/MDS panel, acquired in a standardized way at eight centers over a period of 10 
Sarah Bonte, Rosan Olsman, Sofie Van Gassen, Sergio Matarraz, Neus Villamor, Stefan Nierkens, Paula Fernandez, Elaine Sobral da Costa, Carmen‐Mariana Aanei, Alberto Orfao, Jacques J. M. van Dongen, Yvan Saeys, Mattias Hofmans, Vincent H. J. van der Velden   +13 more
wiley   +1 more source

Uniaxial compressive strength prediction and ratio parameter optimization of titanium tailings composite backfill materials using intelligent hybrid models

Deep Underground Science and Engineering, EarlyView.
Based on the 90 datasets, ERT and four optimization algorithms were used to build four hybrid models to predict the UCS of the backfill body. The SMA‐ERT model was the most effective model, and it can reliably guide the design of the backfill ratio parameters. Abstract This study analyzed the feasibility of using titanium (Ti) tailings as a backfilling
Weijun Liu, Zida Liu, Zhixiang Liu
wiley   +1 more source

Probabilistic prediction of rate‐dependent rock strength using natural gradient boosting and Gaussian process regression

Deep Underground Science and Engineering, EarlyView.
Probabilistic natural gradient boosting and Gaussian process regression models accurately predict rate‐dependent rock strength across lithologies. Static strength and strain rate dominate, while geometric factors have minimal influence, enabling interpretable and uncertainty‐aware predictions for dynamic geomechanical applications. Abstract The dynamic
Hadi Fathipour‐Azar
wiley   +1 more source

Synergistic Interaction Between PEAR1-FGB and the Dominant Role of ABCB1 in Thrombosis Risk: A SHAP and MDR-Based Study in Vietnamese Pedigrees. [PDF]

J Blood Med
Hoang HB, Nguyen TT, Le ANT, Le DH, Do HQ, Nguyen ST, To HTT, Nguyen TTT, Nguyen HMT.   +8 more
europepmc   +1 more source

Explainable hybrid stacking ensemble method for hard rock pillar stability prediction and engineering applications

Deep Underground Science and Engineering, EarlyView.
This research proposes an interpretable hybrid stacking ensemble framework, optimized by the Sparrow Search Algorithm, to enhance hard rock pillar stability prediction. By integrating six machine learning models—k‐nearest neighbors, support vector machines, random forests, Gradient Boosting Decision Tree, eXtreme Gradient Boosting, and Light Gradient ...
Ning Wang, Guoyan Zhao, Meng Wang, Taraka Pattela   +3 more
wiley   +1 more source

A Review of Grain Boundaries: Formation Mechanism, Synthesis Strategy, and Application in Electrocatalysis

EcoEnergy, EarlyView.
An overview of grain boundary engineering in the field of electrocatalysis. ABSTRACT Key electrocatalytic reactions such as HER, OER, ORR, CO2RR, and NRR offer promising routes for storing renewable energy as chemical fuels. However, their widespread application is constrained due to the lack of highly active and stable catalysts. Grain boundaries (GBs)
Jingyu Gao, Fengming Zhou, Xinying Li, Ying Deng, Zexing Wu, Siyuan Feng, Yujing Zhu, Dan Zhang, Zhenyu Xiao   +8 more
wiley   +1 more source

From patterns to predictions: a framework for the spatial epidemiology of wildlife diseases

Ecography, EarlyView.
Wildlife diseases pose a significant threat to biodiversity conservation, public health, and livestock. Spatial epidemiology provides a robust framework to understand disease dynamics and guide policy and management. However, the rapid proliferation of spatial methods has largely occurred in isolation across disciplines, leaving the field without a ...
Cesar Herraiz, Pelayo Acevedo
wiley   +1 more source