Data mining and safety analysis of voriconazole in patients with a hematological malignant tumor based on the FAERS database: differences between children and adults by Hao Li, Hao Li, Manxue Jiang, Manxue Jiang, Xiaona Pan, Lingti Kong, Lingti Kong, Lingti Kong

“…Data mining was done using reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS).ResultsA total of 605 ADEs were included: 116 (19.17%) in children and 489 (80.83%) in adults. …”
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Computing ecosystem risk hotspots: A mediterranean case study by Gianpaolo Coro, Laura Pavirani, Anton Ellenbroek

“…Our results agreed with an alternative Fuzzy C-means-based method (with a 90% to 96% overlap over the years) and a Bayesian regression model (∼80% overlap).Our Mediterranean risk maps can facilitate the development of management and monitoring strategies, supporting the sustainable development and resilience of coastal zones, and can act as prior knowledge for ecosystem models and spatial plans.…”
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Comparison of Hydrus and iStent microinvasive glaucoma surgery implants in combination with phacoemulsification for treatment of open-angle glaucoma: systematic review and network... by Xiaoyu Wang, Rongrong Hu, Dongyu Guo, Nan Hong, Xiuyuan Xuan

“…The network meta-analysis was conducted within a Bayesian framework using the Markov Chain Monte Carlo method in ADDIS software.Results Six prospective RCTs comprising 1397 patients were identified. …”
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Advanced Machine Learning Ensembles for Improved Precipitation Forecasting: The Modified Stacking Ensemble Strategy in China by Tiantian Tang, Yifan Wu, Yujie Li, Lexi Xu, Xinyi Shi, Haitao Zhao, Guan Gui

“…The MSES was then evaluated against the traditional Bayesian model averaging (BMA) approach. Our comprehensive evaluation, based on deterministic forecasting metrics such as the anomaly correlation coefficient (ACC), mean squared skill score (MSSS), and Graded Precipitation Score (Pg), demonstrated the MSES outperformed individual models and the BMA method. …”
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Safety assessment of tolvaptan: real-world adverse event analysis using the FAERS database by Peiyang Cao, Qian Wang, Yan Wang, Qing Qiao, Liyuan Yan

“…ObjectiveThis study aims to analyze the adverse drug events (ADEs) associated with tolvaptan in the Food and Drug Administration Adverse Event Reporting System database from the fourth quarter of 2009 to the second quarter of 2024.MethodsAfter standardizing the data, various signal detection techniques, including Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network, and Multi-Item Gamma Poisson Shrinker, were employed for analysis.ResultsAmong the 7,486 ADE reports where tolvaptan was the primary suspected drug, a total of 196 preferred terms were identified, spanning 24 different system organ classes. …”
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Set-Word Embeddings and Semantic Indices: A New Contextual Model for Empirical Language Analysis by Pedro Fernández de Córdoba, Carlos A. Reyes Pérez, Claudia Sánchez Arnau, Enrique A. Sánchez Pérez

“…Since we adopt an empirical point of view for the semantic issues, we also provide the keys for the interpretation of the results using probabilistic arguments (to facilitate the subsequent integration of the model into Bayesian frameworks for the construction of inductive tools), as well as in fuzzy set-theoretic terms. …”
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High-risk adverse events in two types of single inhaler triple-therapy: a pharmacovigilance study based on the FAERS database by Zhishen Ruan, Chunbin Wang, Shasha Yuan, Yiling Fan, Bo Xu, Xiaodong Cong, Dan Li, Qing Miao

“…We use reporting odds ratio (ROR), proportional reporting ratio (PRR), and Bayesian confidence propagation neural network (BCPNN) for disproportionality analysis. …”
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Downscaling and Projection of Multi-CMIP5 Precipitation Using Machine Learning Methods in the Upper Han River Basin by Ren Xu, Nengcheng Chen, Yumin Chen, Zeqiang Chen

“…This study developed multiple machine learning (ML) downscaling models, based on a Bayesian model average (BMA), to downscale the precipitation simulation of 8 Coupled Model Intercomparison Project Phase 5 (CMIP5) models using model output statistics (MOS) for the years 1961–2005 in the upper Han River basin. …”
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Causal relationship between ulcerative colitis and male infertility: A two-sample Mendelian randomization study. by Xia Wang, Tongyi Li, Qiu Chen

“…MR analysis was performed using MR-Egger regression, the weighted median and the inverse-variance weighted (IVW) respectively, and the causal relationship between UC and male infertility was evaluated by OR and 95% CI, and the Egger-intercept method was used to test for horizontal multiplicity, and the sensitivity analysis was performed using "leave-one-out method". Finally, we used Bayesian Weighted Mendelian Randomization (BWMR) approach to test the results of MR study.…”
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A systematic scoping review of latent class analysis applied to accelerometry-assessed physical activity and sedentary behavior. by Michael Kebede, Annie Green Howard, Yumeng Ren, Blake Anuskiewicz, Chongzhi Di, Melissa A Troester, Kelly R Evenson

“…The criteria to guide the selection of the final number of classes and model fit varied across studies, including Bayesian Information Criterion (63%), substantive knowledge (63%), entropy (50%), Akaike information criterion (50%), sample size (50%), Bootstrap likelihood ratio test (38%), and visual inspection (38%). …”
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Spatiotemporal patterns in precipitation whiplash over China during 1901–2100 based on CMIP6 simulations by Honghao Luo, Nergui Nanding, Fuying Deng, Huan Wu, Zhijun Huang, Junxu Chen, Jiabin Peng, Bin Zhang

“…The Intensity-Duration-Frequency (IDF) curves were estimated by using the nonstationary Generalized Extreme Value (GEV) model combined with Bayesian inference. The results show an increasing trend in frequency, intensity, and severity of precipitation whiplash events, particularly for the long-term future, while the duration of these transitions shows a decreasing trend. …”
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Post-marketing safety surveillance for the recombinant zoster vaccine (Shingrix), vaccine adverse event reporting system, United States, October 2017–April 2024 by Yamin Shu, Wenxin Cheng, Xucheng He, Liu Huang, Wei Chen, Qilin Zhang

“…Descriptive analyses included sex, age, time-to-onset, seriousness, most commonly reported AEs, AE of special interest, and cause of death. The empirical Bayesian data mining was employed to identify potential disproportionalities in reporting. …”
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Deep-Learning-Driven Insights into Nitrogen Leaching for Sustainable Land Use and Agricultural Practices by Caixia Hu, Jie Li, Yaxu Pang, Lan Luo, Fang Liu, Wenhao Wu, Yan Xu, Houyu Li, Bingcang Tan, Guilong Zhang

“…However, the performance improved significantly after integrating the four models with Bayesian optimization (all models had R² > 0.56), which realized quantitative prediction capabilities for nitrate leaching loss concentrations. …”
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Burdens of Tracheal, Bronchus, and Lung Cancer From 1990 to 2021 in China Compared to the Global Projection of 2036: Findings From the 2021 Global Burden of Disease Study by Yuxing Chen, Qingpeng Zeng, Muyu Li, Jiahui Jin, Jun Zhao

“…We also performed Joinpoint regression analysis and Bayesian age‐period‐cohort (BAPC) modeling to project future trends. …”
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A real-world Pharmacovigilance study of brodalumab based on the FDA adverse event reporting system by Ke He, Kaidi Zhao, Tingyi Yin, Meng Liu, Jiashu Liu, Wenqian Du, Xinyi Liu, Baochen Cheng, Dewu Zhang, Yan Zheng

“…Techniques such as the Reporting Odds Ratio, Proportional Reporting Ratio, Multi-item Gamma Poisson Shrinker, and Bayesian Confidence Propagation Neural Network were utilized to analyze the adverse events associated with brodalumab. …”
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ZenLDA: Large-Scale Topic Model Training on Distributed Data-Parallel Platform by Bo Zhao, Hucheng Zhou, Guoqiang Li, Yihua Huang

“…The novelty of ZenLDA consists of three main aspects: (1) it converts the commonly used serial Collapsed Gibbs Sampling (CGS) inference algorithm to a Monte-Carlo Collapsed Bayesian (MCCB) estimation method, which is embarrassingly parallel; (2) it decomposes the LDA inference formula into parts that can be sampled more efficiently to reduce computation complexity; (3) it proposes a distributed LDA training framework, which represents the corpus as a directed graph with the parameters annotated as corresponding vertices and implements ZenLDA and other well-known inference methods based on Spark. …”
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Modeling compositional heterogeneity resolves deep phylogeny of flowering plants by Yongli Wang, Yan-Da Li, Shuo Wang, Erik Tihelka, Michael S. Engel, Chenyang Cai

“…Here we show that, although plastid and mitochondrial genomes lack sufficient phylogenetic signal for resolving deeper phylogeny, the relationships among five mesangiosperm lineages can be confidently resolved under better-fitting models using genome-scale data. According to our Bayesian cross-validation and model test in a maximum likelihood framework, site-heterogeneous models (e.g., CAT-GTR + G4, LG + C20 + F + G) outperform site-homogeneous or partition models often used in previous studies. …”
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Value of Plasma NGAL and Creatinine on First Day of Admission in the Diagnosis of Cardiorenal Syndrome Type 1 by Hao Phan Thai, Bao Hoang Bui, Tien Hoang Anh, Minh Huynh Van

“…Building the optimal regression model (without eGFRCKDEPID1) by the BMA (Bayesian model average) method with two variables NGAL and Creatinine D1, we had the equation: odds ratio = ey while y = −2.39 + 0.0037 × NGAL + 0.17 × Creatinine D1. …”
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Geospatial distribution of Hepatitis E seroprevalence in Nepal, 2021. by Chulwoo Rhee, Amy Dighe, Nishan Katuwal, Haeun Cho, Ramzi Mraidi, Dipesh Tamrakar, Jacqueline KyungAh Lim, Nimesh Poudyal, Il-Yeon Park, Deok Ryun Kim, Ritu Amatya, Rajeev Shrestha, Andrew S Azman, Julia Lynch

“…Seroprevalence and its 95% confidence interval were estimated by age, sex, ecological region, municipality type, and other waterborne-disease related risk factors. Bayesian geostatistical models were fitted to observed seroprevalence data and used to generate high-resolution maps of seroprevalence across Nepal. …”
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Hydrological Models and Artificial Neural Networks (ANNs) to Simulate Streamflow in a Tropical Catchment of Sri Lanka by Miyuru B. Gunathilake, Chamaka Karunanayake, Anura S. Gunathilake, Niranga Marasingha, Jayanga T. Samarasinghe, Isuru M. Bandara, Upaka Rathnayake

“…The ANN model was trained using three well-known training algorithms, namely, Levenberg–Marquadt (LM), Bayesian regularization (BR), and scaled conjugate gradient (SCG). …”
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