Regional and whole-brain neurofunctional alterations during pain empathic processing of physical but not affective pain in migraine patients by Dan Liu, Menghan Li, Heng Jiang, Yiqi Mi, Xiaolei Xu, Yali Zhou, Yaxian Hou, Yuquan Shen, Michael Maes, Xiao Xiao, Feng Zhou, Luca Giani, Keith M. Kendrick, Benjamin Becker, Stefania Ferraro

“…Logistic regression models and machine learning-based classification were employed to determine differences between groups (migraine or control). …”
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Who is WithMe? EEG features for attention in a visual task, with auditory and rhythmic support by Renata Turkeš, Steven Mortier, Jorg De Winne, Jorg De Winne, Dick Botteldooren, Paul Devos, Steven Latré, Tim Verdonck

“…The performance of the different EEG representations is evaluated with the Support Vector Machine (SVM) accuracy on the WithMe data derived from a modified digit span experiment, and is benchmarked against baseline EEG-specific models, including a deep learning architecture known for effectively learning task-specific features.ResultsThe raw EEG time series outperform each of the considered data representations, but can fall short in comparison with the black-box deep learning approach that learns the best features.DiscussionThe findings are limited to the WithMe experimental paradigm, highlighting the need for further studies on diverse tasks to provide a more comprehensive understanding of their utility in the analysis of EEG data.…”
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U-shaped relationship between frailty and non-HDL-cholesterol in the elderly: a cross-sectional study by Yu Pan, Yan Yuan, Juan Yang, Zhu Qing Feng, Xue Yin Tang, Yi Jiang, Gui Ming Hu, Jiang Chuan Dong

“…The variables underwent screening through Least Absolute Shrinkage and Selection Operator (LASSO) regression, univariate logistic regression, and Light Gradient Boosting Machine (LightGBM), with models developed through multivariate logistic regression and the LightGBM algorithm. …”
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Cadmium and selenium blood levels in association with congestive heart failure in diabetic and prediabetic patients: a cross-sectional study from the national health and nutrition... by Renyue Ji, Haisheng Wu, Hongli Lin, Yang Li, Yumeng Shi

“…Logistic regression, weighted quantile sum (WQS), and Bayesian kernel machine learning (BKMR) models were employed to investigate the association between exposure to mixtures of five heavy metals and the odds of having CHF in individuals with diabetes and prediabetes. …”
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A Multimodal Interaction-Driven Feature Discovery Framework for Power Demand Forecasting by Zifan Ning, Min Jin, Pan Zeng

“…TKNFD systematically and automatically aggregates qualitative textual knowledge, expands it into a candidate feature-type set, collects corresponding numerical data for these features, and ultimately constructs four-dimensional multivariate source-tracking databases (4DM-STDs). Subsequently, TKNFD introduces a two-stage quantitative feature identification strategy that operates independently of forecasting models. …”
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Bioinformatics analysis for immune hub genes in BLIS subtype of triple-negative breast cancer by Hend Adel, Manal Abdel Wahed, Heba M. Afify

“…Conclusions Our findings provide a foundation for developing immune-targeted therapeutic approaches for BLIS-TNBC patients and provision the integration of machine learning models to predict treatment responses and optimize patient-specific strategies, potentially transforming the clinical management of this challenging breast cancer subtype.…”
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A novel stemness-related lncRNA signature predicts prognosis, immune infiltration and drug sensitivity of clear cell renal cell carcinoma by Jia Liu, Lin Yao, Yong Yang, Jinchao Ma, Ruijian You, Ziyi Yu, Peng Du

“…The least absolute shrinkage and selection operator (LASSO) in combination with multivariate Cox regression was selected as the optimal approach. …”
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Influence of confining stress on different diameters of disc cutters in rock cutting by Mohammad Ali Torabi, Massoud Palassi, Ghazaleh Ali Mohammadi

“…The failure load is related to the confining stress, cutter diameter, and compressive strength of the rock in a multivariate linear regression model, suggesting that the confining stress is more significant than the other variables. …”
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Association between the lactate dehydrogenase-to-albumin ratio and 28-day mortality in septic patients with malignancies: analysis of the MIMIC-IV database by Yongshi Shen, Kangni Lin, Liuxin Yang, Peng Zheng, Wei Zhang, Jinsen Weng, Yong Ye

“…The primary outcome was 28-day ICU mortality, with secondary outcomes including in-hospital and ICU mortality. Multivariable logistic regression, restricted cubic spline (RCS) analysis, and machine learning models were employed to assess associations between LDAR and outcomes. …”
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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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Changes in Gut Microbiota and Serum Metabolites in Patients with Extreme Obesity by Libuša Kubáňová, Adela Penesová, Ivan Hric, Jana Babjaková, Eva Baranovičová, Marián Grendár, Viktor Bielik

“…Serum metabolites were characterized by nuclear magnetic resonance spectroscopy. Multivariate statistical analysis and Random Forest models were employed to identify predictors with the highest variable importance. …”
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Advances in Infant Cry Paralinguistic Classification—Methods, Implementation, and Applications: Systematic Review by Geofrey Owino, Bernard Shibwabo

“…The overall quality assessment was performed using TRIPOD (Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis) guidelines. …”
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Association between urinary metal concentrations and hyperuricemia in Chinese community-dwelling elderly: Exploring the mediating role of estimating glomerular filtration rate by Zeyang Bai, Yuqing Dai, Siyu Duan, Zhongyuan Zhang, Zhuoheng Shen, Meiyan Li, Limeng Xiong, Jinhao Jia, Yi Zhao, Yihong Di, Huifang Yang, Jian Sun, Rui Zhang

“…The associations between urinary metals and the hyperuricemia were analyzed by multivariable logistic regression model and restricted cubic spline (RCS). …”
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Independent and combined associations of VOCs exposure and MetS in the NHANES 2017–2020 by Xin Gao, Shanshan Xu, Na Lv, Chaokang Li, Ye Lv, Keyi Cheng, Hong Xu

“…We aimed to investigate the association between VOCs and MetS and identify the behavioral patterns in which MetS patients may be exposed to VOCs.MethodsWe conducted a cross-sectional data analysis from 15,560 VOC-exposed participants in the NHANES. Multivariable logistic regression model, weighted quantile sum (WQS) regression model, and Bayesian kernel machine regression (BKMR) regression model were employed to explore chemical exposure`s independent and combined effects on MetS, respectively.ResultsA total of 2,531 individuals were included in our study, of whom 51.28% had MetS and 48.72% were non-MetS. …”
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Gut microbiome alterations and hepatic encephalopathy post-TIPS in liver cirrhosis patients by Shengpeng Li, Zhengguo Xu, Hua Diao, An Zhou, Dianji Tu, Sumin Wang, Yunxuan Feng, Xiaojie Feng, Yi Lai, Shiming Yang, Bo Tang

“…Conclusion Multiple machine learning models revealed that P.vulgatus may serve as a significant predictive microbe for hepatic encephalopathy after TIPS, which may be closely related to its ability to metabolize ammonia. …”
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The predictive value of thyroid hormone sensitivity parameters for cervical lymph node metastasis in patients with differentiated thyroid cancer by Jingcheng Bi, Tianqi Yao, Yu Yao, Zhengcai Zhu, Qiucheng Lei, Lianghe Jiao, Tao Li

“…Statistical analyses including descriptive statistics, comparative analysis, Pearson’s correlation analysis, logistic regression analysis, receiver operating characteristic (ROC) analysis and construction of a multivariable prediction model based on machine learning using the xgbTree method were employed to evaluate the associations and predictive value of thyroid hormone sensitivity parameters for cervical lymph node metastasis.Results The study revealed significant associations between several thyroid hormone sensitivity parameters and cervical lymph node metastasis in patients with DTC. …”
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H-NMR metabolomics identifies three distinct metabolic profiles differentially associated with cardiometabolic risk in patients with obesity in the Di@bet.es cohort by Enrique Ozcariz, Montse Guardiola, Núria Amigó, Sergio Valdés, Wasima Oualla-Bachiri, Pere Rehues, Gemma Rojo-Martinez, Josep Ribalta

“…Then, the association of these clusters with future development of cardiometabolic disease was evaluated using different univariate and multivariate statistical approaches. Moreover, machine learning-based models were built to predict the development of future cardiometabolic disease using BMI and waist-to-hip circumference ratio measures in combination with H-NMR metabolomics. …”
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Association between perfluoroalkyl and polyfluoroalkyl substances and adolescents' sleep disorders: NHANES 2005–2018 by Bocheng Gao, Yanju Gong, Yan Lu, Shuhua Gou, Xingyue Lai, Gan Luo, Hong Yang

“…Eight PFAS compounds were identified. Multivariate logistic regression models, restricted cubic spline (RCS) curves, Bayesian kernel machine regression (BKMR), and weighted quantile sum (WQS) regression were used to assess single, linear, and combined effects on adolescent sleep disorders.ResultsNegative associations were observed between adolescent sleep disorders and three PFAS compounds, specifically perfluorooctanoic acid (PFOA), perfluorooctanesulfonic acid (PFOS), and perfluorononanoic acid (PFNA). …”
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Correlation between metformin use and mortality in acute respiratory failure: a retrospective ICU cohort study by Yunlin Yang, Jinfeng Liu, Yi Hou, Yuxun Wei, Liang Huang, Liang Huang, Wei Wei

“…We applied Kaplan–Meier survival curves, Cox proportional hazards models, and logistic regression to assess associations. …”
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Inter‐ and Intrahospital Price Variation for Common Cardiovascular Admission Diagnoses, Diagnostic Tests, and Therapeutic Procedures by Kriyana P. Reddy, Shreya Mehta, Lauren A. Eberly, Sameed Ahmed M. Khatana, Paula Chatterjee, Alexander C. Fanaroff, Peter W. Groeneveld, Jay Giri, Ashwin S. Nathan

“…Inter‐ and intrahospital price variations were measured using ratios. Multivariate linear mixed‐effects models were fit to determine the association between hospital characteristics and hospital‐level median commercial negotiated rates. …”
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