Development of operational decision support tools for mechanized ski guiding using avalanche terrain modeling, GPS tracking, and machine learning by J. Sykes, J. Sykes, P. Haegeli, R. Atkins, P. Mair, Y. Bühler, Y. Bühler

“…We employed three different modeling approaches to capture the run list decision-making process: Bayesian network, random forest, and extreme gradient boosting. …”
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Multi-Feature Fusion-Based Speech Disorder Classification Using MobileNetV3-EfficientNetB7, Linformer-Performer, and SHAP-Aware XGBoost by Abdul Rahaman Wahab Sait, Suresh Sankaranarayanan, P. Gouthaman

“…Traditional speech disorders (SD) detection relies on subjective analysis, resulting in inconsistent outcome. Direct voice classification lacks effective approaches to capture temporal dependencies. …”
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Association between volatile organic compounds exposure and infertility risk among American women aged 18–45 years from NHANES 2013–2020 by Qiaorui Yang, Jinfu Zhang, Zhenliang Fan

“…As a prevalent environmental pollutant in daily life, there is still a lack of substantial evidence on the association between volatile organic compounds (VOCs) exposure and infertility risk. …”
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Lognormal-Based Sampling for Fission Product Yields Uncertainty Propagation in Pebble-Bed HTGR by Yizhen Wang, Menglei Cui, Jiong Guo, Jinlin Niu, Yingjie Wu, Baokun Liu, Fu Li

“…Therefore, adopting the lognormal-based sampling method is crucial for providing reliable uncertainty analysis results in fission product yields uncertainty analysis.…”
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The disproportionate burden of pulmonary arterial hypertension among the elderly: global, regional, and national trends from 1990 to 2021—findings from the 2021 global burden of di... by Meng Tang, Xingxing Liu, Xiaoyu Hao, Zhiming Liu, Zuwei Li, Hanbin Luo, Guohui Zou, Guohui Zou

“…Analyses included decomposition, health inequality, and frontier analysis. Age-period-cohort (APC) modeling was used to examine period and cohort effects (1990–2021), and future burden was projected using Bayesian APC (BAPC) modeling.ResultsIn 2021, while PAH prevalence and mortality counts were higher than previous years, age-standardized rates (prevalence—ASPR, mortality—ASMR/ASDR) and DALYs showed a declining trend. …”
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Colorectal cancer epidemiology (1990–2050): lessons from the Australasian experience by Bihua Yao, Ying Zhang, Shikun Li, Yu Tian, Milad Ashrafizadeh, Hadi Rastin, Min Tang, Yan Li

“…To forecast CRC mortality until 2050, we utilized a Bayesian Age-Period-Cohort (BAPC) model that includes demographic and temporal factors. …”
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Development of a Transfer Learning-Based, Multimodal Neural Network for Identifying Malignant Dermatological Lesions From Smartphone Images by Jiawen Deng, Eddie Guo, Heather Jianbo Zhao, Kaden Venugopal, Myron Moskalyk

“…Objectives: Early skin cancer detection in primary care settings is crucial for prognosis, yet clinicians often lack relevant training. Machine learning (ML) methods may offer a potential solution for this dilemma. …”
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Interoceptive signals and emotional states shape temporal perception through heart rate modulation by Maria Volodina, Maria Volodina, Anna Rusinova, Kristina Terenteva, Vladimir Kosonogov, Vladimir Kosonogov

“…Emotional video stimuli were used to elicit specific emotional responses, while participants’ attentional focus was manipulated (internal vs. external) to examine its influence on temporal judgments.MethodsWe tested several hypotheses using a combination of linear mixed models and Bayesian mediation analysis. Emotional content, heart rate, attentional focus, and interoceptive accuracy were analyzed for their effects on time perception. …”
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The association between circulating short-chain fatty acids and blood pressure in Chinese elderly population by Jiamou Zhou, Heqiao Zhang, Pengcheng Huo, Huiyan Shen, Qian Huang, Linsheng Yang, Annuo Liu, Guimei Chen, Fangbiao Tao, Kaiyong Liu, Dongmei Zhang

“…Though previous studies have linked SCFAs to blood pressure, there remains a lack of research on the relationship between SCFAs levels in the serum of elderly individuals and blood pressure. …”
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Genetic Structure and Diversity of Eurasian Otter (<i>Lutra lutra</i>) in Northern Eurasia and Caucasus: Are There Any Differences Between the Two Subspecies? by Nadezhda A. Sokolova, Aleksey Yu. Oleynikov, Nikolay P. Korablev, Pavel N. Korablev, Gor A. Kaloyan, Andranik A. Gyonjyan, Andrey N. Korolev, Jose Antonio Hernandez-Blanco, Pavel A. Sorokin

“…The MtDNA median-joining network was mostly star-shaped with a branch of haplotypes from Far Eastern Russian otters. Both mtDNA analysis and Bayesian clustering of microsatellite data indicated that Far Eastern otters are more genetically differentiated than European and Siberian otters (Φst = 0.565 and 0.467; Rst = 0.306 and 0.256), as well as Caucasian otters (<i>L. l. meridionalis</i>) from Russia and Armenia (Φst = 0.515, Rst = 0.253). …”
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Patient Perspectives on Open-Door Policies in Psychiatry: Mixed Methods Study by Timur Liwinski, Robert Davidson, Jan Sarlon, Rainer Gaupp, Lukas Imfeld, Annette B Brühl, Marc Vogel, Christian G Huber, Undine E Lang

“…Traditional qualitative approaches often lack the breadth to fully capture the complexity of these views. …”
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The safety of co-administration of recombinant zoster vaccine (Shingrix) and influenza vaccines in the elderly in VAERS during 2018–2024 by Yihao Li, Huilin Xia, Hong Zhang, Yuan Lu, Hang Zhou, Rongbin Yu, Peng Huang

“…Limitations include VAERS’ passive surveillance nature (underreporting, lack of denominator data), necessitating cautious interpretation and ongoing monitoring.…”
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Model choice for estimating the association between exposure to chemical mixtures and health outcomes: A simulation study. by Lauren Hoskovec, Wande Benka-Coker, Rachel Severson, Sheryl Magzamen, Ander Wilson

“…Bayesian kernel machine regression (BKMR) and nonparametric Bayes shrinkage (NPB) were top-performing methods in our simulation study. …”
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Squamanitaceae and three new species of Squamanita parasitic on Amanita basidiomes by Jian-Wei Liu, Zai-Wei Ge, Egon Horak, Alfredo Vizzini, Roy E. Halling, Chun-Lei Pan, Zhu L. Yang

“…This study reveals that Cystoderma, Phaeolepiota, Squamanita, Floccularia, and Leucopholiota are a monophyletic clade with strong statistical support in Bayesian analysis and form Squamanitaceae. Phaeolepiota nested within Cystoderma; Squamanita, Leucopholiota, and Floccularia clustered together as two monophyletic subclades; and Squamanita was present as a monophyletic clade with strong statistical support in both Maximum Likelihood and Bayesian analyses. …”
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REMAP Periop: a randomised, embedded, multifactorial adaptive platform trial protocol for perioperative medicine to determine the optimal enhanced recovery pathway components in co... by Brian Williams, Jennifer Holder-Murray, Kathirvel Subramaniam, Kert Viele, Oscar C Marroquin, Scott Berry, Aman Mahajan, Luca La Colla, Charles Luke, Alison R Althans, Stephen A Esper, Joshua Knight, Joseph Derenzo, Ryan Ball, Shawn Beaman, Nicholas Schott, Elizabeth Lorenzi, Lindsay R Berry, Miranda Masters, Katie A Meister, Todd Wilkinson, William Garrard

“…The efficacy of an intervention arm within a given domain will be evaluated at regular interim analyses using Bayesian statistical analysis. At the beginning of the trial, participants will have an equal probability of being allocated to any given intervention within a domain (ie, simple 1:1 randomisation), with response adaptive randomisation guiding changes to allocation ratios after interim analyses when applicable based on prespecified statistical triggers. …”
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New records of the colonial chrysophyte Urostipulosphaera articulata (Chrysophyceae, Ochromonadales) in China by Yalu An, Junxue Hao, Fangru Nan, Junping Lv, Qi Liu, Xudong Liu, Shulian Xie, Jia Feng

“…Molecular data and species distribution records for Urostipulosphaera are severely lacking. Species of this genus have been recorded in a few locations in Europe and North America.We identified three samples that were discovered in Shanxi Province, China, based on morphological characteristics and molecular phylogenetic analysis. …”
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A Helping Hand: A Survey About AI-Driven Experimental Design for Accelerating Scientific Research by Lukas Nolte, Sven Tomforde

“…Recent advances in artificial intelligence (AI) and machine learning (ML) offer promising alternatives, but a comprehensive overview of their implementations in experimental design is lacking. This research fills this gap by providing a structured overview and analysis of existing frameworks for AI-driven experimental design, supporting researchers in selecting and developing suitable AI-driven approaches to automate and accelerate their experimental research. …”
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Adverse event profile differences between maribavir and valganciclovir: findings from the FDA adverse event reporting system by Haolin Teng, Shengnan Zhang, Jinyu Yu, Faping Li

“…We applied various disproportionation analysis techniques, including the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN) and multi-item gamma Poisson shrinker (MGPS) algorithms, to identify and quantify potential signals of AEs associated with maribavir and valganciclovir.ResultsThere were 999 and 3,454 reports for maribavir and valganciclovir, respectively. …”
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A prediction method for radiation proctitis based on SAM-Med2D model by Ning Zhang, Haifeng Ling, Wenyu Zhang, Mei Zhang

“…In the other hand, radiomics excels in extracting diagnostically valuable features from medical images but requires extensive manual annotation and often lacks generalizability. Therefore, combining the strengths of deep learning and radiomics is pivotal in addressing these challenges. …”
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The genetic associations of lipidome on bladder cancer: a Mendelian randomization study by Jing Jin, Weihao Wang, Keyuan Zhao, Gang Xu, Chao Peng, Jiajun Chen, Yulei Li, Shouhua Pan

“…The principal technique utilised for the inquiry was the inverse variance-weighted (IVW) meta-analysis. Furthermore, Bayesian weighted Mendelian randomisation (BWMR) was employed to corroborate the findings. …”
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