Differential Diagnosis of Jejunum and Ileum Tumours Based on Video Capsule Endoscopy Data Using Mathematical Analysis by E. D. Fedorov, E. V. Ivanova, S. E. Rauzina, D. E. Seleznev, A. V. Budykina

“…Among them, 8 were found to be statistically significant (affecting the division of objects into groups): patient gender, gut wall/lumen deformation, path of intestinal folds, polypoid changes, vascular pattern, mucosal regularity, mucosal lobulation and colour. Using a Bayesian heterogeneous diagnostic procedure and the calculation of diagnostic factors, a three-level algorithm has been developed for the differential diagnosis of jejunum and ileum lesions.Conclusions. …”
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Exploring the link between exposure to volatile organic chemicals and incidence of infertility:A cross-sectional study by Wen Zhang, Jiarong He, Fang Zhao, Jing Pan, Jiefu Wen, Lijun Jiang, Mingming Zhang

“…In order to comprehensively explore this relationship, various analytical models, including logistic regression, weighted quantile sum (WQS), and Bayesian kernel-machine regression (BKMR), were employed. …”
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Decent Estimate of CME Arrival Time From a Data‐Assimilated Ensemble in the Alfvén Wave Solar Atmosphere Model (DECADE‐AWSoM) by Hongfan Chen, Nishtha Sachdeva, Zhenguang Huang, Bart van derHolst, Ward Manchester IV, Aniket Jivani, Shasha Zou, Yang Chen, Xun Huan, Gabor Toth

“…This enables us to develop a Bayesian framework to filter ensemble simulations using WL observations, which is found to reduce the mean absolute error of CME arrival time prediction from about 13.4 to 5.1 hr. …”
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The influence of anti-COVID-19 measures on the incidence of hand-foot-mouth disease in Zhanggong district of Ganzhou city in China by Yixing Guo, Yuhan Zhu, Yihan Wang, Hui Yin, Laiye Han, Tian Zhong, Ying Xiao, Lawrence T. Lam, Xi Yu

“…The autoregressive integrated moving average model (1, 1, 0) with smallest Bayesian information criteria value as 151.33 was chose for prediction. …”
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Spatiotemporal dynamics and prevention strategies of cervical cancer incidence in Addis Ababa, Ethiopia: an ecological study by Mathewos Assefa, Eva Johanna Kantelhardt, Teferi Gedif Fenta, Tariku Shimels

“…Objective This study analysed the spatial and temporal patterns of cervical cancer incidence in Addis Ababa from 2012 to 2021.Design An ecological study was conducted from 1 September to 30 November 2023 to examine the spatiotemporal trends of cervical cancer incidence.Setting The research was conducted in Addis Ababa, the capital city of Ethiopia.Participants Included were all patients with clinically and/or histopathologically confirmed diagnoses of cervical cancer.Data analysis The study employed advanced analytical tools including R programming, Quantum Geographic Information System V.3.36.0, GeoDa V.1.2.2 and System for Automated Geoscientific Analyses GIS V.9.3.2. Techniques such as Bayesian empirical testing with a block weighting matrix for hotspot identification, Global Moran’s I for spatial autocorrelation, nearest neighbour imputation and universal Kriging interpolation were used to manage data gaps. …”
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Resistance training beyond momentary failure: the effects of past-failure partials on muscle hypertrophy in the gastrocnemius by Stian Larsen, Paul Alan Swinton, Nordis Østerås Sandberg, Benjamin Sandvik Kristiansen, Andrea Bao Fredriksen, Hallvard Nygaard Falch, Roland van den Tillaar, Milo Wolf

“…Data were analysed within a Bayesian framework using a mixed-effect model with random effects to account for the within-participant design. …”
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Patients’ preferences for health insurance coverage of new technologies for treating chronic diseases in China: a discrete choice experiment by Jinsong Geng, Xiaowei Chen, Haini Bao, Danmin Qian, Yuting Shao, Hao Yu

“…Objectives Our study aimed to inform insurance decision-making in China by investigating patients’ preferences for insurance coverage of new technologies for treating chronic diseases.Design We identified six attributes of new medical technologies for treating chronic diseases and used Bayesian-efficient design to generate choice sets for a discrete choice experiment (DCE). …”
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Developing a semi-automated technique of surface water quality analysis using GEE and machine learning: A case study for Sundarbans by Sheikh Fahim Faysal Sowrav, Sujit Kumar Debsarma, Mohan Kumar Das, Khan Mohammad Ibtehal, Mahfujur Rahman, Noshin Tabassum Hridita, Atika Afia Broty, Muhammad Sajid Anam Hoque

“…Key water quality parameters—Sea Surface Temperature (SST), Total Suspended Solids (TSS), Turbidity, Salinity, and pH—were predicted through ML algorithms and interpolated using the Empirical Bayesian Kriging (EBK) model in ArcGIS Pro. The predictive framework leverages Google Earth Engine (GEE) and AutoML, utilizing deep learning libraries to create dynamic, adaptive models that enhance prediction accuracy. …”
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Prognostic and diagnostic accuracy of intracoronary electrocardiogram recorded during percutaneous coronary intervention: a meta-analysis by Jun Fan, Weijie Li, Yizhi Pan, Jialin He, Jiankai Huang, Pingan Chen

“…Summary diagnostic accuracy was obtained by using a Bayesian bivariate random effects model.Results Of the 12 included studies, 7 studies reported the clinical outcomes (821 patients) and 6 studies reported the diagnostic accuracy (485 patients) of IC-ECG. …”
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Genetic insight into dissecting the immunophenotypes and inflammatory profiles in the pathogenesis of Sjogren syndrome by Jingyi Xu, Shucheng Si, Yijun Han, Lin Zeng, Jinxia Zhao

“…We performed a bidirectional Mendelian randomization and mediation study based on randomly allocated instrumental variables to infer causality, followed by external validation with UK Biobank data and Bayesian colocalization. Results We demonstrated that an elevated level of CD27 on IgD + CD24 + B cell, a subset of B cells expressing both IgD and CD24, was associated with a higher risk of SS (OR = 1.119, 95% CI: 1.061–1.179, P < 0.001), while CD3 on CD45RA + CD4 + Treg was a protective factor (OR = 0.917, 95%CI: 0.877–0.959, P < 0.001). …”
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Multiple Dimensions Define Thresholds for Population Resilience of the Eastern Oyster, Crassostrea virginica by Megan K. La Peyre, Hongqing Wang, Shaye E. Sable, Wei Wu, Bin Li, Devin Comba, Carlos Perez, Melanie Bates, Lauren M. Swam

“…Two statistical approaches were applied, with each model highlighting a different operational definition of a threshold: random forest models identified a threshold as an abrupt change in the oyster abundance‐ salinity relationship, while Bayesian models identified an increased probability of oyster abundance dropping below a critical threshold, defined here as less than 50% of the 5‐year mean. …”
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Variability of daily feed intake as an indicator of resilience in Pietrain pigs by C. Casto-Rebollo, P. Nuñez, S. Gol, J. Reixach, N. Ibáñez-Escriche

“…Progeny mortality was calculated for each contemporary group (farm and batch) of the offspring, and sires were classified into three levels of resilience. A Bayesian linear model was used to determine whether the differences in progeny mortality rate between the levels of resilience were relevant. …”
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Spatiotemporal models with confounding effects: application on under-five mortality across four sub-Saharan African countries by Haile Mekonnen Fenta, Haile Mekonnen Fenta, Ding-Geng Chen, Ding-Geng Chen, Temesgen T. Zewotir, Najmeh Nakhaei Rad

“…Therefore, the main aim of this study is to adopt a spatiotemporal dynamic model that includes the confounding effects between time, space, and their interactions with fixed covariates, with a special emphasis on U5M across disconnected sSA countries.MethodWe used nationally publicly representative Demographic and Health Survey (DHS) data for the period from 2000 to 2020. Bayesian spatiotemporal hierarchical modeling with an integrated nested Laplace approximation (INLA) program was used to model the spatiotemporal distribution of U5M among children across 37 districts located in four disconnected sSA regions: Ethiopia, Nigeria, Zimbabwe, and Ghana.ResultsA total of 170,356 under-five children from 37 districts were considered, and 15,467 died before the age of five. …”
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Genetic analysis of Pinna rudis L 1758 (Mollusca, Bivalvia, Pinnidae) in the Northwest Cabo Verde Islands (Central-East Atlantic) by Evandro P. Lopes, Sarah Santos, Raquel Xavier, Joana L. Santos, M. Pilar Cabezas, Fernando Sequeira, António M. Santos

“…We found significant genetic divergence between the population from Cabo Verde and the other sampled population, suggesting that P. rudis is not monotypic, but may include several cryptic species. Bayesian and maximum-likelihood phylogenetic analysis, including all Pinnidae species, indicated that P. rudis from Gorée Island (Senegal) and Baía das Gatas (São Vicente Island) might be undergoing speciation. …”
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Quantifying the sources and health risks of groundwater nitrate via dual NO isotopes and Monte Carlo simulations in a developed planting-breeding area by Jianwei Liu, Shuo Qiao, Shilong Zhao, Hui Chen, Yong Wu, Donghao Li, Ping Liu, Ling Li

“…Analysis by combining stable isotopes (δ15N-NO3− and δ18O-NO3−) with the Bayesian isotope mixing model (MixSIAR) revealed that soil N (60.3 %) and manure and sewage (35.9 %) contributed the most NO3− in groundwater, followed by chemical N fertilizer (2.9 %) and atmospheric N deposition (0.8 %). …”
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Evolution of gender representation among Canadian OTL-HNS residents: a 27-year analysis by Sarah Chorfi, Joseph S. Schwartz, Neil Verma, Meredith Young, Lawrence Joseph, Lily H. P. Nguyen

“…Descriptive analysis was used to examine gender representation among OTL-HNS residents across years, and to compare these trends with other specialties. Bayesian hierarchical models were fit to analyze the growth in program rates in OTL-HNS based on gender. …”
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The Global Burden and Trends of Legionella spp. Infection-Associated Diseases from 1990 to 2021: An Observational Study by Yonghong Zhong, Linfeng Shen, Yan Zhou, Yibo Sun, Xiaofang Fu, Huaqiong Huang

“…Methods Age-standardized disability-adjusted life years (ASR-DALYs) and age-standardized death rates (ASDRs) of LSIADs from 1990 to 2021 were accessed from the Global Burden of Disease (GBD) 2021, which utilized the Bayesian hierarchical meta-regression tool and the Cause of Death Ensemble model to estimate these metrics. …”
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Incremental long-term benefit of drug therapies for chronic obstructive pulmonary disease in quality of life but not mortality: a network meta-analysis by Qiong Pan, Jiongzhou Sun, Shiyuan Gao, Zian Liu, Yiwen Huang, Yixin Lian

“…The comparative efficacy of 4 drugs and their combinations in acute exacerbation and mortality was assessed using Bayesian network meta-analysis models. Results This network meta-analysis identified 69 eligible RCTs on 7 classes of drug therapies after stepwise screening and included 125,331 COPD patients. …”
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Petrophysical Regression regarding Porosity, Permeability, and Water Saturation Driven by Logging-Based Ensemble and Transfer Learnings: A Case Study of Sandy-Mud Reservoirs by Shenghan Zhang, Yufeng Gu, Yinshan Gao, Xinxing Wang, Daoyong Zhang, Liming Zhou

“…To guarantee the predicting quality of LightGBM, continuous restricted Boltzmann machine (CRBM) and Bayesian optimization (Bayes) are introduced as assistants to enhance the significance of input logs and the setting of employed hyperparameters. …”
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DENND5B Gene Expression as a Trigger for the Development of Diabetes Mellitus–Peripheral Artery Disease: Insights from a Univariate and Multivariate Mendelian Randomization Study by Qiaoqiao Li, Fuli Cao, Xueping Gao, Yuan Xu, Bo Li, Tianyang Hu

“…Method: To identify candidate hub genes and develop insights into the pathogenesis of DM-PAD, we employed a comprehensive approach encompassing two-sample Mendelian Randomization (two-sample MR), summary data-based Mendelian randomization (SMR), and Bayesian colocalization (COLOC) methods. These methodologies facilitated the integration of summary-level data derived from genome-wide association studies of DM-PAD with expression quantitative trait locus (eQTLs) studies conducted on blood samples. …”
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