Association between dietary multi-metal intake and the risk of diabetic retinopathy: a population-based study by Chaohua Zhang, Haiyang Peng, Qin Lang, Haoyu Fang, Keqin Zhang, Andong Zhao

“…Associations between the intake of six dietary metals and DR risk were assessed using multivariable logistic regression, Weighted Quantile Sum (WQS) regression, and Bayesian Kernel Machine Regression (BKMR). …”
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Association between albumin-corrected anion gap and delirium in acute pancreatitis: insights from the MIMIC-IV database by Yuanshuo Ge, Youran Ma, Peng Lv, Junhao Ren, Zhe Wang, Cheng Zhang

“…Among the machine learning models, the Random Forest achieved superior predictive accuracy (AUC = 0.81), and SHAP analysis highlighted ACAG as a primary determinant in model prediction. …”
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Multidimensional assessment of sustainability and competitiveness in the ceramic tile and natural stone industries: a cross-country comparative study by Reza Yarahmadi, Ali Asghar Asadi

“…SHAP analysis, applied to a multivariate regression model, identified CO₂ emissions as the most influential factor driving structural pressure, highlighting its significance in climate-focused policymaking. …”
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Can mutation abundance assess the biological behavior of BRAF V600E-positive papillary thyroid carcinoma? by Yeqin Ni, Ping Song, Xiangfeng Lin, Jingjing Shi, Qian Shi, Yuanhui Li, Siyu Zhu, Tianhan Zhou, Yanping Xun, Shirong Zhang, Xingchang Ren, Kaining Lu, Fan Wu, Wei Wang, Pan Zhao, Rongjing Zhou, Wenhua Zhang, Dandan Li, Jiaoping Zhang, Chuanghua Chen, Linlin Mao, Li Zhou, Gang Pan, You Peng, Yunxian Yu, Yuying Chen, Rong Ni, Guhan Luo, Yu Zhang, Jugao Fang, Haitao Zheng, Dingcun Luo

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A Deep Learning Model for Identifying the Risk of Mesenteric Malperfusion in Acute Aortic Dissection Using Initial Diagnostic Data: Algorithm Development and Validation by Zhechuan Jin, Jiale Dong, Chengxiang Li, Yi Jiang, Jian Yang, Lei Xu, Ping Li, Zhun Xie, Yulin Li, Dongjin Wang, Zhili Ji

“…The training and internal validation cohort consisted of 450 patients from Beijing Anzhen Hospital, whereas the external validation cohort comprised 75 patients from Nanjing Drum Tower Hospital. Three machine learning models were developed: the benchmark model using laboratory parameters, the multiorgan feature–based AAD complicating MMP (MAM) model based on computed tomography angiography images, and the integrated model combining both data modalities. …”
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Combine photosynthetic characteristics and leaf hyperspectral reflectance for early detection of water stress by Linbao Li, Linbao Li, Linbao Li, Guiyun Huang, Guiyun Huang, Guiyun Huang, Jinhua Wu, Jinhua Wu, Jinhua Wu, Yunchao Yu, Yunchao Yu, Yunchao Yu, Guangxin Zhang, Guangxin Zhang, Guangxin Zhang, Yang Su, Yang Su, Yang Su, Xiongying Wang, Xiongying Wang, Xiongying Wang, Huiyuan Chen, Huiyuan Chen, Huiyuan Chen, Yeqing Wang, Di Wu, Di Wu, Di Wu

“…Reflectance in 540-560nm and 750-1100nm and selected SVI such as Simple Ratio (SR)752/690 can track drought responses effectively before leaves showed drought symptoms. Multivariate Linear Regression (MLR) and three machine learning algorithms, namely Random Forest (RF), Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) were employed to develop models for estimating LCC and ChlF parameters. …”
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Compressive Strength Prediction Using Coupled Deep Learning Model with Extreme Gradient Boosting Algorithm: Environmentally Friendly Concrete Incorporating Recycled Aggregate by Mayadah W. Falah, Sadaam Hadee Hussein, Mohammed Ayad Saad, Zainab Hasan Ali, Tan Huy Tran, Rania M. Ghoniem, Ahmed A. Ewees

“…The developed approach is compared to the well-known artificial intelligence (AI) approaches named multivariate adaptive regression spline (MARS), extreme learning machines (ELMs), and random forests (RFs). …”
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Morphometric differences between basal cell carcinomas & melanomas of the head & neck versus other sites and their influence on neural networks by Jonas Hue, Jinendra Ekanayake, Jamshid Dehmeshki, Jagtar Dhanda

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Nondestructive estimation of leaf chlorophyll content in banana based on unmanned aerial vehicle hyperspectral images using image feature combination methods by Weiping Kong, Weiping Kong, Lingling Ma, Huichun Ye, Huichun Ye, Jingjing Wang, Chaojia Nie, Binbin Chen, Xianfeng Zhou, Wenjiang Huang, Zikun Fan

“…We proposed two methods of image feature combination for banana LCC inversion, which are a two-pair feature combination and a multivariable feature combination based on four machine learning algorithms (MLRAs).ResultsThe results indicated that compared to conventionally used VIs alone, the banana LCC estimations with both proposed VI and TF combination methods were all significantly improved. …”
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Development and validation of a LASSO logistic regression based nomogram for predicting live births in women with polycystic ovary syndrome: a retrospective cohort study by Yue Liu, Jingshu Gao, Hang Ge, Hang Ge, Jiaxing Feng, Yu Wang, Xiaoke Wu, Xiaoke Wu

“…The mean-filling method was used to address missing data, and Lasso-Logistic regression was combined with machine learning models to identify the most significant predictors of live births. …”
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A Framework for Gold Price Prediction Combining Classical and Intelligent Methods with Financial, Economic, and Sentiment Data Fusion by Gergana Taneva-Angelova, Stefan Raychev, Galina Ilieva

“…This study presents a hybrid framework for multivariate gold price prediction that integrates classical econometric modelling, traditional machine learning, modern deep learning methods, and their combinations. …”
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Study of grain spreading and cooling process based on non equilibrium thermal simulation by ZHAO Chao, CHEN Tao, ZHOU Zhonglin, YANG Jian

“…ObjectiveTo improve the automation level of 0the temperature control of grain cooling.MethodsUsing SST k-ω turbulence model and non-equilibrium thermal model to conduct theoretical analysis. …”
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MRI-based risk factors for intensive care unit admissions in acute neck infections by Jari-Pekka Vierula, Harri Merisaari, Jaakko Heikkinen, Tatu Happonen, Aapo Sirén, Jarno Velhonoja, Heikki Irjala, Tero Soukka, Kimmo Mattila, Mikko Nyman, Janne Nurminen, Jussi Hirvonen

“…Machine learning models (random forest, XGBoost, support vector machine, neural networks) were tested. …”
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Urinary metal levels and their association with Parkinson’s disease risk: insights from NHANES 2013–2020 by Jia-jie Lv, Jia-jie Lv, Xin-yu Li, Xin-yu Li, Cheng-hao Yang, Cheng-hao Yang

“…The metals with the highest weight in the WQS model were Mo (56.79%), Co (34.20%), Ba (3.33%), and Tu (3.27%). …”
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A predictive model for functional cure in chronic HBV patients treated with pegylated interferon alpha: a comparative study of multiple algorithms based on clinical data by Ya-mei Ye, Yong Lin, Fang Sun, Wen-yan Yang, Lina Zhou, Chun Lin, Chen Pan

“…Abstract Background A multivariate predictive model was constructed using baseline and 12-week clinical data to evaluate the rate of clearance of hepatitis B surface antigen (HBsAg) at the 48-week mark in patients diagnosed with chronic hepatitis B who are receiving treatment with pegylated interferon α (PEG-INFα). …”
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Volatile organic compounds exposure associated with sarcopenia in US adults from NHANES 2011–2018 by Pangbo Wang, Pangbo Wang, Pangbo Wang, Wei Chen, Hongwei Fang, Liwei Xu, Jun Zhao, Jing Huang

“…We also employed Weighted Quantile Sum (WQS) regression model, a high-dimensional statistical approach used to evaluate the joint effects of multiple exposures, and Bayesian Kernel Machine regression (BKMR) model, a combination of Bayesian and statistical learning methods, to assess the mixture effects of mVOCs on sarcopenia risk. …”
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Association between the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio and mortality among hypertension patients by Xiaozhou Su, Huiqing Rao, Chunli Zhao, Jiehua Wu, XianWei Zhang, Donghua Li

“…Machine learning algorithms were used to establish a prediction model. …”
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A hybrid framework: singular value decomposition and kernel ridge regression optimized using mathematical-based fine-tuning for enhancing river water level forecasting by Iman Ahmadianfar, Aitazaz Ahsan Farooque, Mumtaz Ali, Mehdi Jamei, Mozhdeh Jamei, Zaher Mundher Yaseen

“…Hence, a novel hybrid model is provided, incorporating singular value decomposition (SVD) in conjunction with kernel-based ridge regression (SKRidge), multivariate variational mode decomposition (MVMD), and the light gradient boosting machine (LGBM) as a feature selection method, along with the Runge–Kutta optimization (RUN) algorithm for parameter optimization. …”
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Association of mixed polycyclic aromatic hydrocarbons exposure with cardiovascular disease and the mediating role of inflammatory indices in US adults by Tingwei Du, Xiaoli Shen, Runqing Zhan

“…Adults with a diagnosis of CVD and seven monohydroxylated PAH metabolites (OH-PAHs) in their urine samples were included. Multivariate logistic regression and Bayesian kernel machine regression (BKMR) models were used to estimate the association between single and mixed PAHs exposure and CVD. …”
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Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intellig... by Gary S Collins, Lily Peng, Johannes B Reitsma, Lotty Hooft, Ben Van Calster, Jie Ma, Maarten van Smeden, Andrew L Beam, Constanza L Andaur Navarro, Paula Dhiman, Karel GM Moons, Patricia Logullo

“…Introduction The Transparent Reporting of a multivariable prediction model of Individual Prognosis Or Diagnosis (TRIPOD) statement and the Prediction model Risk Of Bias ASsessment Tool (PROBAST) were both published to improve the reporting and critical appraisal of prediction model studies for diagnosis and prognosis. …”
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