Clinical diagnostic and prognostic value of homocysteine combined with hemoglobin [f (Hcy-Hb)] in cardio-renal syndrome caused by primary acute myocardial infarction by Min-Juan Zeng, Yan-Quan Liu, Ping Pang, Xiao-Jun Chen, He Huang, Rui-Na Huang, Shi-Sen Li, He-Hui Zhang, Yue Yin, Chang-Sen Wang, Jin-Da Lin, Lin Lin, Shao-Peng Chen, Li Xu, Liang-Qing Zhang

“…Consequently, we integrated these two factors into a machine learning model to evaluate its diagnostic and prognostic value for CRS, providing novel insights for clinical and nursing practices. …”
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The association of exposure to multiple metals with the risk of idiopathic oligoasthenoteratozoospermia: The mediating role of sperm chromatin by Tao Yin, Sen Liang, XinYu Zhou, Xueting Lai, Xun Su, Jiajing Tao, Shiwei Ren, Danyang Li, Yunxia Cao, Dongmei Ji, Chunmei Liang

“…The individual effect of each metal on high sperm DFI, high sperm HDS, and iOAT risk was explored using multivariate logistic regression models. Quantile g-computation (Qgcomp) and Bayesian kernel machine regression (BKMR) were applied to dissect the combined effects of these metals on high sperm DFI, high sperm HDS, and iOAT risk. …”
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Investigation of the relationship between lead exposure in heavy metals mixtures and the prevalence of stroke: a cross-sectional study by Jiarong He, Wen Zhang, Fang Zhao, Ming Wang, Zhuo Wang, Chen Liang, Jing Pan, Jiaoying Jia, Mingming Zhang

“…After adjusting for covariates, a multivariable logistic regression model identified a positive association between the logarithmic concentration of Pb and the incidence of stroke. …”
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Differential impacts of physical activity volume and intensity on blood lead levels in children and adolescents: a cross-sectional study by Shengrong Ouyang, Yan Yin, Yuanyuan Li, Jianxin Wu, Zhuo Liu

“…BLLs were natural log-transformed (ln-BLL) for analysis. Weighted multivariable linear regression, general additive models, mediation analysis, and Bayesian kernel machine regression (BKMR) were employed to explore associations. …”
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Associations of per- and polyfluoroalkyl substances in follicular fluid with polycystic ovarian syndrome in infertile women may be mediated by sex hormones by Yating Bian, Yingxiao Yue, Yufan Cheng, Dan Wang, Lu He, Peixia Yan, Huan Song, Tong Wang, Weidong Zhou, Xu Zhang, Zhizhen Pan, Liangpo Liu, Liangpo Liu

“…Bayesian kernel machine regression (BKMR) model was utilized to evaluate the associations between joint and individual PFAS exposure and PCOS. …”
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Derivation and external validation of a risk score for predicting HIV-associated tuberculosis to support case finding and preventive therapy scale-up: A cohort study. by Andrew F Auld, Andrew D Kerkhoff, Yasmeen Hanifa, Robin Wood, Salome Charalambous, Yuliang Liu, Tefera Agizew, Anikie Mathoma, Rosanna Boyd, Anand Date, Ray W Shiraishi, George Bicego, Unami Mathebula-Modongo, Heather Alexander, Christopher Serumola, Goabaone Rankgoane-Pono, Pontsho Pono, Alyssa Finlay, James C Shepherd, Tedd V Ellerbrock, Alison D Grant, Katherine Fielding

“…<h4>Methods and findings</h4>We used Botswana XPRES trial data for adult HIV clinic enrollees collected during 2012 to 2015 to develop a parsimonious multivariable prognostic model for active prevalent TB using both logistic regression and random forest machine learning approaches. …”
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Association between volatile organic compounds exposure and cardiometabolic function: a population-based study by Qiuyu Wang, Yongping Cao, Fei Ma, Hengyang Zhang, Yuelin Hu, Wenwen Xiao

“…BKMR (bayesian kernel machine regression), WQS (weighted quantile sum), and Q-gcomp (quantile g-computation) models were employed to explore the association between VOC mixture exposure and CMI. …”
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The association of life’s essential 8 with prevalence of chronic respiratory diseases in adults: insights from NHANES 2007–2018 by Liu Fen, Li Yan, Zhao Fei, Kuai Zhong-Kai, You Ya-Yu, Hong Xiu-Qin, Wen Si-Ao, Liu Zheng-Yu, Pan Hong-Wei

“…Subgroup analyses and machine learning models were also conducted. Results Among 20,537 participants included (mean age, 48.02 ± 16.73 years), 10,492 (51.08%) were female and 3812 (18.56%) were determined to have CRDs. …”
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Association of non-phthalate plasticizer exposure during early pregnancy with gestational diabetes mellitus: The potential mediation effect of plasma lipidome by Yingying Mao, Shuqin Tang, Huan Liu, Qing Huang, Da Chen, Yuanyuan Li, Fengjiang Sun, Wei Huang

“…In addition, the Bayesian kernel machine regression (BKMR) model further revealed a joint effect of the non-PAE mixture exposure on GDM risk, and DMAZ and diisobutyl adipate/dibutyl adipate (DiBA/DnBA) were identified as key contributors to the joint effect. …”
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Serum analytes as predictors of disease recurrence and the duration of invasive disease-free survival in patients with triple negative breast cancer enrolled in the OXEL trial trea... by Renee N Donahue, Jeffrey Schlom, Nicole J Toney, Claudine Isaacs, Filipa Lynce, Candace Mainor, Megan T Lynch

“…Furthermore, logistic regression and Cox proportional hazard models, developed using machine learning methods, demonstrated that combinations of serum analytes were more predictive of disease recurrence and iDFS duration than analyses of single serum analytes. …”
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Cross-sectional design and protocol for Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights (AI-READI) by Gerald McGwin, Linda M Zangwill, Nicholas Evans, Shannon McWeeney, Cecilia S Lee, Bhavesh Patel, Jeffrey C Edberg, Cynthia Owsley, Aaron Lee, Cecilia Lee, Sally L Baxter, Michael Snyder, Samantha Hurst, Nicole Ehrhardt, Christopher Chute, Dawn S Matthies, Julia P Owen, Amir Bahmani, Sally Baxter, Edward Boyko, Aaron Cohen, Jorge Contreras, Garrison Cottrell, Virginia de Sa, Jeffrey Edberg, Irl Hirsch, Michelle Hribar, T.Y. Alvin Liu, Bonnie Maldenado, Sara Singer, Bradley Voytek, Joseph Yracheta, Linda Zangwill

“…Following Findable, Accessible, Interoperable, Reusable principles, AI-READI can be viewed as a model for future efforts to develop other medical/health data sets targeted for AI/ML. …”
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Advanced graph embedding for intelligent heating, ventilation, and air conditioning optimization: An ensemble learning-based recommender system by Shouliang Lai, Xiyu Yi, Peiling Zhou, Lu Peng, Wentao Liu, Shi Sun, Binrong Huang

“…Utilizing advanced graph embedding techniques combined with ensemble learning models, we developed a recommender system tailored for Heating, Ventilation, and Air Conditioning (HVAC) optimization in Shenzhen Qianhai Smart Community. …”
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Diagnostic Value of F-FDG PET/CT Radiomics in Lymphoma: A Systematic Review and Meta-Analysis by Chaoying Liu MD, Jun Zhao PhD, Heng Zhang PhD, Xinye Ni PhD

“…Introduction Various machine learning models and features have been proposed for lymphoma diagnosis using 18 F-fluorodeoxyglucose ( 18 F-FDG) PET/CT radiomics. …”
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Understanding mental health among university students in Kenya: what role do family support and age play? by Bylhah Mugotitsa, Bylhah Mugotitsa, Reinpeter Momanyi, Joseph Kuria, David Amadi, Jacob Masai, Eric Angula, Benjamin Tsofa, Benjamin Tsofa, Jay Greenfield, Jim Todd, Agnes Kiragga

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Development and validation of the Immune Profile Score (IPS), a novel multiomic algorithmic assay for stratifying outcomes in a real-world cohort of patients with advanced solid ca... by Yan Liu, Matthew Zibelman, Timothy Chan, Justin Guinney, Douglas Adkins, Ezra E W Cohen, Michelle M Stein, Halla Nimeiri, Sandip P Patel, Alia D Zander, Rossin Erbe, Ailin Jin, Sayantoni Mukhopadhyay, Ben Terdich, Mario G Rosasco, Nirali Patel, Chithra Sangli, Timothy Taxter, Seung Won Hyun, Brett M Mahon, A Kate Sasser, Michelle A Ting-Lin, Kyle A Beauchamp

“…Additionally, IPS remained significant in multivariable models controlling for TMB, MSI, and PD-L1, with IPS HRs of 0.49 (90% CI 0.42 to 0.56), 0.47 (90% CI 0.41 to 0.53), and 0.45 (90% CI 0.38 to 0.53), respectively. …”
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Environmental exposure to perchlorate, nitrate, and thiocyanate in relation to biological aging in U.S. adults, a cross-sectional NHANES study by Weiliang Kong, Yina Jin

“…Weighted Quantile Sum (WQS) and Bayesian Kernel Machine Regression (BKMR) models examined PNT mixtures.Results8,368 participants were analyzed. …”
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Association between admission Braden Skin Score and delirium in surgical intensive care patients: an analysis of the MIMIC-IV database by Meiling Shang, Meiling Shang, Ailing Shang, Yu Xu, Yu Xu

“…Feature importance of BSS was initially assessed using a machine learning algorithm, while restricted cubic spline (RCS) models and multivariable logistic analysis evaluated the relationship between BSS and delirium. …”
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Physiological serum uric acid concentrations correlate with arterial stiffness in a sex-dependent manner by Oliver Thews, Thomas Schmid, Alexander Kluttig, Andreas Wienke, Melanie Zinkhan, Wolfgang Ahrens, Till Bärnighausen, Hermann Brenner, Stefanie Castell, Berit Lange, Wolfgang Lieb, Karin Halina Greiser, Marcus Dörr, Lilian Krist, Stefan N. Willich, Volker Harth, Nadia Obi, Michael Leitzmann, Annette Peters, Börge Schmidt, Matthias B. Schulze, Henry Völzke, Matthias Nauck, Stephanie Zylla, Anke Hannemann, Tobias Pischon, Ilais Moreno Velásquez, Matthias Girndt, Claudia Grossmann, Michael Gekle

“…This correlation was more pronounced in women than in men. In multivariable linear regression models, we observed an association of uric acid (mmol/l) with PWV (m/s) of β = 1.12 (95% confidence interval (CI): 0.78; 1.45) in males and β = 1.35 (1.05; 1.66) in females, independent of other factors known to affect vascular stiffness. …”
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Toward improving retention in HIV care after pregnancy: lessons from a post-pandemic cohort in the United States by Alexandra H. Latham, Alexandra H. Latham, Alexandra H. Latham, Andrea Lugo Morales, Andrea Lugo Morales, Andrea Lugo Morales, Elizabeth Barba Gutierrez, Elizabeth Barba Gutierrez, Elizabeth Barba Gutierrez, Michael Jochum, Michael Jochum, Sarah Conrad, Sarah Conrad, Eva H. Clark, Kassandra Goytia, Megan Alam, Jessica Gerard, Jessica Gerard, Jennifer McKinney, Jennifer McKinney, Jennifer McKinney

“…Variables were analyzed using descriptive statistics, and Kaplan-Meier curves were used to assess viral suppression during pregnancy and the first year postpartum. A Random Forest machine learning model was used to determine variables of relative importance for prediction of adequate RIC. …”
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Associations between phenol and paraben exposure and the risk of developing breast cancer in adult women: a cross-sectional study by Yao Xiong, Zhiyu Li, Xiong Xiong, Zixuan Luo, Kaixin Zhong, Jiawei Hu, Shengrong Sun, Chuang Chen

“…The results from the weighted multivariable regression models indicated that exposure to elevated concentrations of TRS increased the risk of developing BC by 2.33 (Q2: 95% CI = 1.45–3.75, p < 0.001) and 1.94 times (Q3: 95% CI = 1.21–3.09, p = 0.006), respectively. …”
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