Machine learning model interpretability using SHAP values: Applied to the task of classifying and predicting the nutritional content of different cuts of mutton by Li Wang, Xuchun Sun, Jing Liang, Zhiyuan Ma, Fei Li, Shengyan Hao, Baocang Liu, Long Guo, Xiuxiu Weng

“…SHAP value analysis revealed that lipid-related variables and wavelengths in the 2300–2500 nm region were major contributors to the model. …”
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Nutrient Balance of Citrus Across the Mandarin Belts of India by Anoop Kumar Srivastava, Ambadas Dattatray Huchche, Leon-Etienne Parent, Suresh Kumar Malhotra, Vasileios Ziogas, Lohit Kumar Baishya

“…The diagnosis could also be conducted at a local scale, thanks to the Euclidian geometry and additivity of <i>clr</i> and <i>wlr</i> variables.…”
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Analysis of imperfect interfaces in cobalt ferrite plates using a linear spring model: a comparative study with terfenol-D by Seema, Abhinav Singhal

“…Methodology To achieve this, the study employs a variable-separable technique following Direct Sturm-Liouville method and appropriate boundary conditions to derive frequency relations for both magnetically open and short circuit scenarios. …”
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Comparison between response surface methodology and Taguchi method for dyeing process parameters optimization in fabric manufacturing by empirical planning by D. Nikhila Sri, Rajyalakshmi Kottapalli, A. Pavani, Charankumar Ganteda, E. Gouthami, Assmaa Abd-Elmonem, Samah Abdelati Haroun, Syed M. Hussain, Mustafa Bayram, Abdulrazak H. Almaliki

“…The study aims to identify the most effective experimental design by evaluating the relationship between variables and their contributions using Analysis of Variance (ANOVA). …”
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Optimized gallium extraction from Bayer liquor using ion exchange: Experimental modeling in batch mode and demonstration in continuous columns by Hesamoddin Gorzin, Mohadeseh Babaei Layaei, Mojtaba Dehghani, Mehrdad Mahmoudi, Salman Movahedirad

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The Impact of Kefir Consumption on Inflammation, Oxidative Stress Status, and Metabolic-Syndrome-Related Parameters in Animal Models: A Systematic Review and Meta-Analysis by Zahid Naeem Qaisrani, Wai Phyo Lin, Bo Bo Lay, Khin Yadanar Phyo, Myat Mon San, Nurulhusna Awaeloh, Sasithon Aunsorn, Rinrada Pattanayaiying, Susakul Palakawong Na Ayudthaya, Choosit Hongkulsup, Nirunya Buntin, Sasitorn Chusri

“…Nevertheless, preclinical results have been variable. This systematic review and meta-analysis aimed to assess the influence of kefir and its derived compositions on parameters associated with MetS, inflammation, and oxidative stress in rodent studies. …”
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Exploring the connection between maternal mental health and partnership, parental role, and satisfaction with various aspects of life using pairfam data: a cross-sectional analysis by Monique Förster, Claudia Kirsch, Julia Habermann, Dorothee Noeres

“…Multiple linear regression analysis was conducted, with the mental health composite scale of the Short Form 12 (Version 2.0) Health Survey as the dependent variable, and the previously mentioned variables as independent variables. …”
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Bioelectrical impedance analysis of bone mineral content based on dual-energy X-ray absorptiometry: evaluation of age-stratified optimized models by YoungJin Moon, Zheng Dong, Sang Ki Lee, Hwi-yeol Yun, JuWon Song, Min Ju Shin, DuBin Im, JiaHao Xu, XuanRu Wang

“…A total of 302 healthy Korean participants (148 men and 154 women; mean ages 24.87 ± 12.43 and 34.98 ± 22.24 years, respectively) underwent body composition measurements via BIA and DXA. Basic variables such as age, height, and weight, along with a range of BIA parameters, were utilized to refine predictive models for BMC. …”
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Machine learning-based construction of a programmed cell death-related model reveals prognosis and immune infiltration in pancreatic adenocarcinoma patients by Bing Wang, Zhida Long, Xun Zou, Zhengang Sun, Yuanchu Xiao

“…Using a comprehensive machine learning framework involving 117 algorithmic combinations under a Leave-one-out cross-validation (LOOCV) strategy, we identified the StepCox[both] + Ridge as the best algorithms composition to construct a prognostic model based on six PCDRGs, ITGA3, CDCP1, IL1RAP, CLU, PBK, and PLAU. …”
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A hybrid fuzzy logic–Random Forest model to predict psychiatric treatment order outcomes: an interpretable tool for legal decision support by Alexandre Hudon, Alexandre Hudon, Alexandre Hudon, Alexandre Hudon

“…Feature importance was also computed to assess the influence of each variable on the prediction outcome.ResultsThe hybrid model achieved an accuracy of 98.1%, precision of 93.3%, recall of 100%, and a F1 score of 96.6. …”
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Quantitative modeling of mortality patterns in dogs exposed to alpha particle emitting radionuclides: Insights from competing risks and causal inference machine learning. by Eric Wang, Igor Shuryak, David J Brenner

“…Using a Causal Forest model, which is designed to detect causal relationships rather than just associations, we investigated the causal impact of radioactivity on dog mortality, accounting for other variables. …”
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Modeling Whole-Plant Carbon Stock in <i>Olea europaea</i> L. Plantations Using Logarithmic Nonlinear Seemingly Unrelated Regression by Yungang He, Weili Kou, Ning Lu, Yi Yang, Chunqin Duan, Ziyi Yang, Yongjun Song, Jiayue Gao, Weiyu Zhuang

“…Secondly, in the CS compatibility model system, the total CS model of <i>Olea europaea</i> L. was constructed by the Logarithmic Nonlinear Seemingly Unrelated Regression (LNSUR) method with <i>D</i> and <i>D</i>²<i>H</i> as independent variables. …”
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Identification and optimization of relevant factors for chronic kidney disease in abdominal obesity patients by machine learning methods: insights from NHANES 2005–2018 by Xiangling Deng, Lifei Ma, Pin Li, Mengyang He, Ruyue Jin, Yuandong Tao, Hualin Cao, Hengyu Gao, Wenquan Zhou, Kuan Lu, Xiaoye Chen, Wenchao Li, Huixia Zhou

“…To explore the associations between these variables and CKD, the present study used a multivariable-adjusted least absolute shrinkage and selection operator (LASSO) regression model, along with a restricted cubic spline (RCS) model. …”
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Methods of evaluation the quality of teaching in higher education institutions by Irina V. Barannikova, Elena N. Shaforostova

“…The method of quality assessment and the results of the study, based on the proposed pyramid model of quality assessment with the details of the components, included in its composition, and the designation of their values for evaluation are considered in the paper. …”
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Multi-trait phenotypic modeling through factor analysis and bayesian network learning to develop latent reproductive, body conformational, and carcass-associated traits in admixed... by Muhammad Anas, Bin Zhao, Bin Zhao, Haipeng Yu, Carl R. Dahlen, Kendall C. Swanson, Kris A. Ringwall, Lauren L. Hulsman Hanna

“…Using exploratory and confirmatory FA, Body Size (BS) and Body Composition (BC) were identified as UBT for Model 1, explaining 14 phenotypic traits (t = 14). …”
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The Graft of ANN-FEM Technique in Macro-mechanics of Multi-oriented Natural Fiber/Polyester Laminates by Christian Emeka Okafor, Christopher Chukwutoo Ihueze

“…A standard feed-forward backpropagation network was adopted and the ANN model consists of stacking sequence, laminate aspect ratio and fiber orientation as input variables while the selected network outputs variables include average stress and displacement. …”
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Major Adverse Kidney Events in Hospitalized Older Patients With Acute Kidney Injury: Machine Learning–Based Model Development and Validation Study by Xiao-Qin Luo, Ning-Ya Zhang, Ying-Hao Deng, Hong-Shen Wang, Yi-Xin Kang, Shao-Bin Duan

“…The Boruta algorithm was used to select the most important predictor variables from 53 candidate variables. The eXtreme Gradient Boosting algorithm was applied to establish a prediction model for MAKE30. …”
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Assessing the Success of Ferula assa-foetida L. Plantation Restoration Operations in Semi-Steppe Rangelands by Linking Plant Functional Traits to Species Diversity by Esfandiar Jahantab, Azam Khosravi Mashizi, Mohsen Sharafatmandrad

“…Structured equation modeling allowed for the study of important individual species in vegetation composition with Assafoetida's mediating role. …”
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Dynamic Cascade Spiking Neural Network Supervisory Controller for a Nonplanar Twelve-Rotor UAV by Cheng Peng, Guanyu Qiao, Bing Ge

“…Unknown variables in the environment, such as wind disturbance during a flight, affect the accurate trajectory of multi-rotor UAVs. …”
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Development and Validation of a Machine Learning Prediction Model for Textbook Outcome in Liver Surgery: Results From a Multicenter, International Cohort by Jane Wang, MD, Amir Ashraf Ganjouei, MD, MPH, Taizo Hibi, MD, PhD, Nuria Lluis, MD, PhD, Camilla Gomes, MD, Fernanda Romero-Hernandez, MD, Han Yin, BA, Lucia Calthorpe, MD, Yukiyasu Okamura, MD, PhD, Yuta Abe, MD, PhD, Shogo Tanaka, MD, PhD, Minoru Tanabe, MD, PhD, Zeniche Morise, MD, PhD, Horacio Asbun, MD, PhD, David Geller, MD, Mohammed Abu Hilal, MD, PhD, Mohamed Adam, MD, Adnan Alseidi, MD, EdM, International Hepatectomy Study Group, Alison Baskin, Annie Wong-On-Wing, Annie Yang, Devesh Sharma, Taisuke Imamura, Masanori Nakamura, Yuya Miura, Koki Hayashi, Masatsugu Ishii, Keita Shimata, Kazuya Hirukawa, Hiroki Ueda, June S. Peng, Lucas Thornblade, Kenzo Hirose, Kimberly Kirkwood, Eric Nakakura, Carlos Corvera, Ajay Maker

“…This study aimed to (1) develop a machine learning (ML) model that predicts the textbook outcome in liver surgery (TOLS) using preoperative variables and (2) validate the TOLS criteria by determining whether TOLS is associated with long-term survival after hepatectomy. …”
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