Results 71 to 80 of about 56,385 (212)

A Markov approach to credit rating migration conditional on economic states

Canadian Journal of Statistics, EarlyView.
Abstract We develop a model for credit rating migration that accounts for the impact of economic state fluctuations on default probabilities. The joint process for the economic state and the rating is modelled as a time‐homogeneous Markov chain. While the rating process itself possesses the Markov property only under restrictive conditions, methods ...
Michael Kalkbrener, Natalie Packham
wiley   +1 more source

Epilepsy Phenotypic Spectrum of NUS1‐Related Disorder: A Case Series

Annals of the Child Neurology Society, EarlyView.
ABSTRACT Background Epilepsy with myoclonic and atonic seizures (EMAtS), also known as Doose syndrome, accounts for 1%–2% of childhood epilepsies, and various genes have been implicated in causing this epilepsy syndrome. NUS1 encodes for Nogo‐B receptor (NgBR), which stabilizes the dehydrodolichyl‐diphosphate synthase complex in the endoplasmic ...
Saumel Ahmadi, Natalie Fulton, Michael Morrissey, Rebekah Landre, Stuart Tomko, Fumihiko Urano, Réjean M Guerriero   +6 more
wiley   +1 more source

Prognostic Implication of CYP2C19 Genotype According to Clinical Risk Stratification After Drug‐Eluting Stent Implantation

Clinical Pharmacology &Therapeutics, EarlyView.
From the nationwide multicenter consortium, 8,163 patients undergoing drug‐eluting stent implantation were classified according to the presence of the CYP2C19 loss‐of‐function (LoF) allele: rapid or normal metabolizers (RMs/NMs) vs. intermediate or poor metabolizers (IMs/PMs), and clinical risk was stratified using the CHADS‐P2A2RC and TRS 2°P scores ...
Hyun Woong Park, Jae‐Hwan Lee, Jin‐Ok Jeong, Diana A. Gorog, Udaya S. Tantry, Byeong‐Keuk Kim, Hyung Joon Joo, Kiyuk Chang, Jin‐Yong Hwang, Young Bin Song, Sung Gyun Ahn, Jung‐Won Suh, Woong Gil Choi, Jung Rae Cho, Jeehoon Kang, Sang Yeub Lee, Hyo‐Soo Kim, Moo Hyun Kim, Do‐Sun Lim, Eun‐Seok Shin, Paul A. Gurbel, Young‐Hoon Jeong, on behalf of the PTRG‐DES Consortium Investigators   +22 more
wiley   +1 more source

Improving Genotype Imputation in High‐Dimensional Pharmacogenomics Using Multiple Imputation: Evaluation with Machine Learning Approaches

Clinical Pharmacology &Therapeutics, EarlyView.
Multiple imputation is well‐established for handling missing data, yet its use in high‐dimensional genetic datasets remains limited. Using pharmacokinetic tuberculosis simulations and SNP data (1000 Genomes Project), we compared machine learning (ML) and traditional approaches (e.g., mean imputation and complete‐case analysis) for imputation and ...
Innocent G. Asiimwe, Tao You, Daniel F. Carr, Munir Pirmohamed, Geraint Davies, Andrea L. Jorgensen, on behalf of the UNITE4TB Consortium   +6 more
wiley   +1 more source

Clinical Safety of Extended Interval Dosing of Nivolumab in Patients with Melanoma

Clinical Pharmacology &Therapeutics, EarlyView.
Extended interval dosing regimens of immune checkpoint inhibitors have been implemented widely. However, their approval was mainly based on pharmacokinetic modeling and simulations. Consequently, comparative safety data of extended interval dosing regimens in a real‐world setting are limited.
Ruben Malmberg, Maaike M. Hofman, Fatima Ashad, Alaa Daloul, Stefani Oosterveld, Edwin A. Basak, Esther Oomen‐de Hoop, Astrid A. M. van der Veldt, Arjen Joosse, Roelof W. F. van Leeuwen, Ron H. J. Mathijssen   +10 more
wiley   +1 more source

Assessing Overall Survival Benefits in Advanced Cancers: The Role of External Comparator Cohort Studies with Real‐World Data

Clinical Pharmacology &Therapeutics, EarlyView.
External comparator cohort (ECC) studies with real‐world data (RWD) may provide more reliable estimates of treatment differences compared to single‐arm trials (SAT), yet they face limitations such as selection bias and data heterogeneity. This study assessed the perceived strength of evidence of ECC studies compared to SAT and randomized controlled ...
Francesco Pignatti, Tarec Christoffer El‐Galaly, Martin Kaiser, Kimmo Porkka, Robin Doeswijk, Peter Mol, Donna R. Rivera, Catherine C. Lerro, Ulrich‐Peter Rohr, Patrice Verpillat, Antonios Valachis, Dario Trapani, Massimo Di Maio, Nicola Latino, Raul Cordoba, Nathan Cherny, Miriam Koopman, Diogo Martins‐Branco, George Pentheroudakis, Douwe Postmus   +19 more
wiley   +1 more source

Board Composition, Sustainability Reporting, and the Moderating Role of a Contextual Issue: Evidence From an Emerging Country

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT This study examines the impact of board composition (BC) on sustainability reporting (SR) in financial firms listed on the Dhaka Stock Exchange (DSE), with a focus on the moderating role of non‐performing loans (NPLs). Using 421 firm‐year observations from 49 firms (2016–2024) and an ordinary least squares (OLS) regression model, the results ...
Sumon Kumar Das, Prome Akter
wiley   +1 more source

Bridging Theory and Prediction: A Hybrid SEM and Machine Learning Approach to Optimize Lean Construction for Megaproject Sustainability in China

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Construction megaprojects, large‐scale, complex, and capital‐intensive, are particularly prone to inefficiencies, cost overruns, delays, and environmental degradation due to fragmented workflows, stakeholder misalignment, and resource intensity.
Abdelazim Ibrahim, Tarek Zayed, Zoubeir Lafhaj, Ahmed Maged, Ahmed Farouk Kineber, Jingchao Yang   +5 more
wiley   +1 more source

Probability prediction of true‐triaxial compressive strength of intact rocks based on the improved PSO‐RVM model

Deep Underground Science and Engineering, EarlyView.
In this work, we propose an improved particle swarm optimization (PSO) algorithm and develop an improved PSO‐relevance vector machine (RVM) model as a substitute for traditional true‐triaxial testing. The model's high prediction accuracy was validated through comparisons with two other machine learning methods and five three‐dimensional Hoek–Brown type
Qi Zhang, Maohui Wang, Ning Wang, Yixin Shen, Xuzhen He   +4 more
wiley   +1 more source

Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN

Deep Underground Science and Engineering, EarlyView.
A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan, Chenxi Yin, Guangdong Yang, Shengyong Ding, Bin Tian   +4 more
wiley   +1 more source