Effect of the exposure to brominated flame retardants on hyperuricemia using interpretable machine learning algorithms based on the SHAP methodology. by Yu Cai, Xi-Ru Huang, Sheng-Jia Wang, Ying-Chao Liang, De-Liang Liu, Shu-Fang Chu, Hui-Lin Li

“…Weighted quantile sum (WQS) regression was performed to assess collective mixture sum impact, along with contributions of each component. Nine machine-learning models were developed for hyperuricemia prediction, and six discrimination characteristics were applied to select the optimal model. …”
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Machine learning integrates region-specific microbial signatures to distinguish geographically adjacent populations within a province by Li Luo, Li Luo, Bangwei Chen, Bangwei Chen, Shengyin Zeng, Shengyin Zeng, Yaxin Li, Yaxin Li, Xiaolin Chen, Xiaolin Chen, Jianguo Zhang, Xiangjie Guo, Shujin Li, Lei Ruan, Shida Zhu, Cairong Gao, Cuntai Zhang, Tao Li

“…However, the gut microbiota variations among people residing in different regions within a province remain enigmatic.MethodsShotgun metagenomics sequencing was performed to analyze the gut microbiota of 381 unrelated Chinese Han individuals living in two cities (Wuhan and Shiyan) of Hubei Province. To obtain the optimal model that can distinguish geographically close populations, three machine learning (ML) algorithms based on microbiota or functions were employed.ResultsSignificant differences in microbial α diversity and β diversity were observed. …”
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Auxiliary Diagnosis of Pulmonary Nodules’ Benignancy and Malignancy Based on Machine Learning: A Retrospective Study by Wang W, Yang B, Wu H, Che H, Tong Y, Zhang B, Liu H, Chen Y

“…The dataset was split 70%/30%, and stratified five-fold cross-validation was applied to the training set. The optimal model was interpreted with SHAP to identify the most influential predictive features.Results: This study enrolled 3355 patients, including 1156 with benign and 2199 with malignant pulmonary nodules. …”
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Machine learning-based radiomics for differentiating lung cancer subtypes in brain metastases using CE-T1WI by Xueming Xia, Wei Du, Qiheng Gou

“…Through a multistep selection process, a refined subset of 15 optimal radiomic features was identified for model training. …”
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Geographically Weighted Random Forest Based on Spatial Factor Optimization for the Assessment of Landslide Susceptibility by Feifan Lu, Guifang Zhang, Tonghao Wang, Yumeng Ye, Qinghao Zhao

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Machine Learning based estimation of Chlorophyll and Flavonoid content in Bitter Leaf using Color and GLCM Texture Features by Retno Damayanti, Yusuf Hendrawan, Sandra Sandra

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Building a machine learning-assisted echocardiography prediction tool for children at risk for cancer therapy-related cardiomyopathy by Lindsay A. Edwards, Christina Yang, Surbhi Sharma, Zih-Hua Chen, Lahari Gorantla, Sanika A. Joshi, Nicolas J. Longhi, Nahom Worku, Jamie S. Yang, Brandy Martinez Di Pietro, Saro Armenian, Aarti Bhat, William Border, Sujatha Buddhe, Nancy Blythe, Kayla Stratton, Kasey J. Leger, Wendy M. Leisenring, Lillian R. Meacham, Paul C. Nathan, Shanti Narasimhan, Ritu Sachdeva, Karim Sadak, Eric J. Chow, Patrick M. Boyle

“…We explored the feasibility and optimal processes for machine learning-enhanced cardiomyopathy prediction in survivors using serial echocardiograms from five centers. …”
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Artificial Intelligence and Machine Learning Approaches for Target-Based Drug Discovery: A Focus on GPCR-Ligand Interactions by M. O. Otun

“…This review explores the integration of AI and ML techniques in GPCR-targeted drug discovery, highlighting their potential to accelerate lead identification, optimize ligand binding predictions, and improve structure-activity relationship modeling. …”
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Improve the Intelligent Convenience of Multivariate Optimization of Concrete Mix Ratio and the Development of Corresponding Applications by Zhanfei Yang, Bin Chen, Jianfen Zhou, Saihua Huang

“…In order to be more efficient in the optimization of concrete mixture, a new intelligent optimization model of concrete mixture was established by using particle swarm optimization on the basis of the original optimization model, and the specific performance was fitted and predicted by using the support vector machine. …”
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Evaluating Maize Residue Cover Using Machine Learning and Remote Sensing in the Meadow Soil Region of Northeast China by Zhengwei Liang, Jia Du, Weilin Yu, Kaizeng Zhuo, Kewen Shao, Weijian Zhang, Cangming Zhang, Jie Qin, Yu Han, Bingrun Sui, Kaishan Song

“…The Google Earth Engine (GEE) and remote sensing images from 2019 to 2023 were used to obtain spectral characteristics before the maize seedling stage in Northeast China, followed by constructing the CRC estimation models using machine learning algorithms. To avoid the impact of multicollinearity among data, three machine learning algorithms—ridge regression (RR), partial least squares regression (PLSR), and least absolute shrinkage and selection operator (LASSO)—were employed. …”
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Nonlinear effects of traffic statuses and road geometries on highway traffic accident severity: A machine learning approach. by Yao Liang, Hongxia Yuan, Zhenwu Wang, Zhongjin Wan, Tiantian Liu, Bing Wu, Shijie Chen, Xiaobo Tang

“…Using this dataset, we tested the classification performance of four machine learning models, including eXtreme Gradient Boosting, Gradient Boosted Decision Tree, Random Forest, and Light Gradient Boosting Machine. …”
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High precision water quality retrieval in Dianchi Lake using Gaofen 5 data and machine learning methods by Yuewen Feng, Jun Zhang, Sanjie Guo, Yunbai Zhang, Zhongwei Zhang

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Predicting Wastewater Characteristics Using Artificial Neural Network and Machine Learning Methods for Enhanced Operation of Oxidation Ditch by Igor Gulshin, Nikolay Makisha

“…The SMAPE score of 1.052% on test data demonstrates the model’s accuracy and highlights the potential of integrating artificial neural networks (ANN) and machine learning (ML) with mechanistic models for optimizing wastewater treatment processes. …”
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Artificial Intelligence in Chronic Disease Management for Aging Populations: A Systematic Review of Machine Learning and NLP Applications by Feng G, Weng F, Lu W, Xu L, Zhu W, Tan M, Weng P

“…The rise of artificial intelligence (AI) technology (eg, machine learning, deep learning, NLP, computer vision) offers possibilities for improving Geriatric Chronic Disease Management, including optimizing the distribution of medical resources, supplementing professional management teams, popularizing health education, optimizing medication management, enhancing psychological support, improving medical insurance efficiency and accuracy, and strengthening family support. …”
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Effective DDoS attack detection in software-defined vehicular networks using statistical flow analysis and machine learning. by Himanshi Babbar, Shalli Rani, Maha Driss

“…By leveraging a minimal subset of features from a given dataset, a comparative study is conducted to determine the optimal sample size for maximizing model accuracy. …”
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LEVERAGING MACHINE LEARNING ALGORITHMS TO IDENTIFY POTENTIAL GEOSITES FOR GEOTOURISM PROMOTION IN ZIZ UPPER WATERSHED IN SOUTHEASTERN MOROCCO by Lahbib NAIMI, Mohamed MANAOUCH, Abdeslam JAKIMI

“…Initia lly, a comprehensive inventory of 120 geomorphosites was conducted, and precise measurements of three topographical parameters were taken at each site. Subsequently, the machine learning algorithm, namely Bagging was employed to develop predictive model. …”
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Review of Demand Response-based Optimal Scheduling of Electric and Thermal Integrated Energy Systems by Jingshan MO, Guangxian YAN, Na SONG, Mingyang YUAN

“…However, the long offline training time for machine learning algorithms requires further optimization. …”
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Optimized wavelength selection for eggplant seed vitality classification using information acquisition techniques by Bing Yang, Xuyang Liu, Dongfang Zhang, Dongfang Zhang, Xiaofei Fan, Xiaofei Fan, Bo Peng, Jun Zhang, Jun Zhang

“…Seed vigor classification models were developed using Extreme Learning Machine (ELM), Random Forest (RF), and Support Vector Machine (SVM).The optimal classification accuracies achieved were 90.0% for ELM, 91.45% for RF, and 90.5% for SVM. …”
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Method of optimization of decision-making during management of safety of flights in the activities of operators of aerodromes by S. A. Tolstykh

“…Along with the safety indicator, an indicator of financial damage from recorded events is used, which is calculated in value terms taking into account direct and indirect damage to the aerodrome operator. Regression modeling is used in conjunction with the decision-making technique of “human-machine procedures”. …”
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Optimization of the control system of BP-PID rice polishing unit based on WAO algorithm by HUANG Jinliang, ZHOU Jin, YU Wei

“…ObjectiveAddress the current issues of poor internal flow stability, low single-machine efficiency, and subpar polishing quality in rice polishing units.MethodsFirstly, the traditional polishing machine was improved, its control parameters were clarified, and the mathematical model of the rice polishing unit was established. …”
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