Global, regional, and national burden of anxiety disorders during the perimenopause (1990–2021) and projections to 2035 by Ying Zhang, Ting-Ting Hu, Yong-Ran Cheng, Zhi-Fen Zhang, Jun Su

“…We calculated trends using the estimated average percent change, and future projections were made using the Bayesian age–period–cohort model to estimate disability-adjusted life year trends for anxiety disorders from 2022 to 2035. …”
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Forecasting Rice Productivity and Production of Odisha, India, Using Autoregressive Integrated Moving Average Models by Rahul Tripathi, A. K. Nayak, R. Raja, Mohammad Shahid, Anjani Kumar, Sangita Mohanty, B. B. Panda, B. Lal, Priyanka Gautam

“…Prediction was made for the immediate next three years, that is, 2007-08, 2008-09, and 2009-10, using the best fitted ARIMA models based on minimum value of the selection criterion, that is, Akaike information criteria (AIC) and Schwarz-Bayesian information criteria (SBC). The performances of models were validated by comparing with percentage deviation from the actual values and mean absolute percent error (MAPE), which was found to be 0.61 and 2.99% for the area under rice in Odisha and India, respectively. …”
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Association of Alzheimer’s and Lewy body disease pathology with basal forebrain volume and cognitive impairment by Julia Schumacher, Stefan Teipel, Alexander Storch

“…Associations of regional volumes with pathological markers (Braak stage, CERAD score, and McKeith criteria for LB pathology) and cognitive performance were assessed using Bayesian statistical methods. Results We included people with autopsy-confirmed pure AD (N = 248), pure LBD (N = 22), and mixed AD/LBD (N = 185). …”
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Combination of an E-Nose and an E-Tongue for Adulteration Detection of Minced Mutton Mixed with Pork by Xiaojing Tian, Jun Wang, Zhongren Ma, Mingsheng Li, Zhenbo Wei

“…The discrimination results were evaluated and compared by canonical discriminant analysis (CDA) and Bayesian discriminant analysis (BAD). It was shown that the capability of discrimination of the combined system (classification error 0%∼1.67%) was superior or equable to that obtained with the two instruments separately, and E-tongue system (classification error for E-tongue 0∼2.5%) obtained higher accuracy than E-nose (classification error 0.83%∼10.83% for E-nose). …”
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Typhoon Maria Precipitation Retrieval and Evolution Based on the Infrared Brightness Temperature of the Feng-Yun 4A/Advanced Geosynchronous Radiation Imager by Gen Wang, Kefu Wang, Wei Han, Dongyong Wang, Xuexing Qiu

“…The contribution rate of the brightness temperature at different channels to the objective function of precipitation retrieval model was obtained by the Bayesian model averaging (BMA). Based on the preliminary experimental “quantification” evaluation index, we concluded that the method adopted in this paper can be used to retrieve precipitation in infrared data and to retrieve the spiral cloud rain bands of a typhoon. …”
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An analysis of the global burden of gallbladder and biliary tract cancer attributable to high BMI in 204 countries and territories: 1990–2021 by Zhuowen Hu, Xue Wang, Xin Zhang, Wuping Sun, Jun Mao

“…The disease burden was forecasted through 2035 using the Bayesian age period cohort (BAPC) model.ResultsGlobally, ASMR and ASDR for GBTCs related to high BMI decreased from 1990 to 2021; however, the absolute number of deaths and DALYs cases more than doubled, and similar patterns are projected to continue over the next 14 years in the absence of intervention. …”
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Population Dynamics of the Exotic Flatworm Obama nungara in an Invaded Garden by Shanèze Noël, Yoan Fourcade, Virginie Roy, Georges Bonnet, Lise Dupont

“…Daily monitoring data revealed high population size fluctuations that may be explained by meteorological factors as well as intra‐ and inter‐specific interactions. Bayesian modeling confirmed that O. nungara's abundance fluctuates depending on temperature, humidity, and precipitation. …”
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ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool by D. Di Santo, C. He, F. Chen, L. Giovannini

“…This tool leverages the strengths of multiple regression-based and probabilistic machine learning methods, including LASSO (see the list of abbreviations in Appendix B), support vector machine, classification and regression trees, random forest, extreme gradient boosting, Gaussian process regression, and Bayesian ridge regression. These regression algorithms are used to construct computationally inexpensive surrogate models to effectively predict the impact of input parameter variations on model output, thereby significantly reducing the computational burden of running high-fidelity models for sensitivity analysis. …”
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Divergence of alpine plant populations of three Gentianaceae species in the Qinling sky Island by Peng-Cheng Fu, Bing-Jie Mo, He-Xin Wan, Shu-Wen Yang, Rui Xing, Shan-Shan Sun

“…Divergence time estimation based on plastomes and approximate Bayesian computation based on genomic SNPs showed that Qinling populations of the three Gentianaceae species originated at different periods under various patterns including primary source and hybridization. …”
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2b-RAD genotyping for population genomic studies of Chagas disease vectors: Rhodnius ecuadoriensis in Ecuador. by Luis E Hernandez-Castro, Marta Paterno, Anita G Villacís, Björn Andersson, Jaime A Costales, Michele De Noia, Sofía Ocaña-Mayorga, Cesar A Yumiseva, Mario J Grijalva, Martin S Llewellyn

“…Preliminary population genomic analyses (global AMOVA and Bayesian clustering) were implemented. Our results showed that the 2b-RAD genotyping protocol is effective for R. ecuadoriensis and likely for other triatomine species. …”
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Chromosome 1 Sequence Analysis of C57BL/6J-Chr1KM Mouse Strain by Fuyi Xu, Tianzhu Chao, Yiyin Zhang, Shixian Hu, Yuxun Zhou, Hongyan Xu, Junhua Xiao, Kai Li

“…We then performed sequence similarity and Bayesian concordance analysis using the SNPs identified on Chr 1 and their counterparts in three subspecies, Mus musculus domesticus, M. m. musculus, and M. m. castaneus. …”
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Web-Based Healthcare Delivery Integrated System to Forecast COVID-19 Hospitalizations in a Marginalized Patient Population: A Case Study in Broome County, New York by Anemone Kasasbeh, Elie Issa, Naseem Khan, Mehmet Yildirim, Amy Booth, Hiroki Sayama

“…The candidate model was selected based on the akaike information criterion, Bayesian information criterion, and the root-mean-square error (RMSE). …”
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Impact of bedaquiline resistance probability on treatment decision for rifampicin-resistant TB by T.P.H. Trang, R. Kessels, T. Decroo, A. Van Rie

“…BACKGROUND: Accurate diagnosis of bedaquiline (BDQ) resistance remains challenging. A Bayesian approach expresses this uncertainty as a probability of BDQ resistance (prBDQR) with a 95% credible interval. …”
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A Dynamic Discretization Algorithm for Learning BN Model: Predicting Causation Probability of Ship Collision in the Sunda Strait, Indonesia by Iis Dewi Ratih, Ketut Buda Artana, Heri Kuswanto, Dhimas Widhi Handani, Renata Zahabiya

“…The contributing factors to ship collisions include weather conditions, technical failure, insufficient resources, navigation errors, human error, and the failure of other vessels. The Bayesian Network (BN) machine learning method is capable of predicting ship collisions. …”
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Development and validation of machine-learning models for predicting the risk of hypertriglyceridemia in critically ill patients receiving propofol sedation using retrospective dat... by Jiawen Deng, Hemang Yadav, Kiyan Heybati

“…Six ML algorithms will be tuned and evaluated. Bayesian optimisation will be used for hyperparameter selection. …”
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Changing trends in lung cancer disease burden between China and Australia from 1990 to 2019 and its predictions by Dan Zhao, Haijun Mu, Ping Yu, Chao Deng

“…Materials and Methods The data from the 2019 Global Burden of Disease Study were used to analyze disease temporal trends using Joinpoint regression model. The Bayesian age‐period‐cohort model was used for prediction. …”
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Long-term trends in the burden of pulmonary arterial hypertension in China and worldwide: new insights based on GBD 2021 by Zhehao Xu, Jia Ding, Ruiyun Liang, Shuangfeng Xie

“…Understanding the trends and factors contributing to PAH is crucial for developing effective public health strategies.MethodsThis study utilized data from the Global Burden of Disease (GBD) 2021 database to estimate the burden of PAH in China and worldwide from 1990 to 2021. A Bayesian age-period-cohort (BAPC) model was employed to analyze differences in PAH burden across age, gender, and time periods, and to project global epidemiological trends until 2036.ResultsFrom 1990 to 2021, the incidence and prevalence of PAH in China increased by 80.59% and 86.74%, respectively. …”
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Strength prediction of ECC-CES columns under eccentric compression using adaptive sampling and ML techniques by Khaled Megahed

“…The novelty of this work lies in integrating adaptive sampling through Bayesian Optimization (BO) with the power of machine learning (ML) to generate training data that effectively covers a large input space while minimizing error. …”
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Simulation-based validation of a method to detect changes in SARS-CoV-2 reinfection risk. by Belinda Lombard, Harry Moultrie, Juliet R C Pulliam, Cari van Schalkwyk

“…To assess the performance of the catalytic model, we simulated reinfection datasets that incorporated different processes that may bias inference, including imperfect observation and mortality. A Bayesian approach was used to fit the model to simulated data, assuming a negative binomial distribution around the expected number of reinfections, and model projections were compared to the simulated data using different magnitudes of change in reinfection risk. …”
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Comparative Analysis of the Reported Animal-Vehicle Collisions Data and Carcass Removal Data for Hotspot Identification by Xiaoxue Yang, Yajie Zou, Lingtao Wu, Xinzhi Zhong, Yinhai Wang, Muhammad Ijaz, Yichuan Peng

“…To complete the objective, both the Negative Binomial (NB) model and the generalized Negative Binomial (GNB) are applied in calculating the Empirical Bayesian (EB) estimates using the animal collision data collected on ten highways in Washington State. …”
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