Development and validation of a nomogram for predicting in-hospital mortality in older adult hip fracture patients with atrial fibrillation: a retrospective study by Zhenli Li, Jing He, Tiezhu Yao, Guang Liu, Jing Liu, Ling Guo, Mengjia Li, Mengjia Li, Zhengkun Guan, Zhengkun Guan, Ruolian Gao, Jingtao Ma

“…Logistic regression (LR) and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms were employed to screen features. We further used Extreme Gradient Boosting (XGBoost) based on features selected by LR and LASSO algorithms to assist in identifying the final model-established features. …”
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SUMOylation-related genes define prognostic subtypes in stomach adenocarcinoma: integrating single-cell analysis and machine learning analyses by Kaiping Luo, Kaiping Luo, Donghui Xing, Donghui Xing, Xiang He, Yixin Zhai, Yanan Jiang, Hongjie Zhan, Zhigang Zhao

“…A SUMOylation Risk Score (SRS) model was developed using 69 machine learning models across 10 algorithms, with performance evaluated by C-index and AUC. …”
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Identification and analysis of neutrophil extracellular trap-related genes in periodontitis via bioinformatics and experimental verification by Miao Yu, Zhenqi Ye, Zixin Ye, Yaping Wu, Xiang Wu

“…Then, machine learning algorithms were exploited to screen hub NRGs, and a predictive model was constructed based on these hub NRGs. …”
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Identification of anoikis-related genes classification patterns and immune infiltration characterization in chronic rhinosinusitis with nasal polyps based on machine learning by Ziqi Chen, Lingmei Qu, Qing Hao, Shuang Teng, Shuo Liu, Qin Wu, Hongtian Yi, Xianji Shen, Liang Li, Zhaonan Xu, Yanan Sun

“…Immune cell infiltration was analysed using the CIBERSORT algorithm. CRSwNP samples were classified via consensus clustering. …”
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Research Progress and Prospect of Green Infrastructure with Public Health Promotion Function by Tongyu LI, Junyi LIXU, Binxia XUE, Yan (USA) SONG

“…To manage the multidimensionality of GI research, cluster analysis is performed using a Word2Vec model combined with a K-means algorithm to integrate different GI forms into a coherent classification system.ResultsThe results show that GI can be clearly divided into different categories, such as urban green spaces and parks, high-interaction spaces, trees in built-up areas, water management and biofiltration systems, community and residential greening, green roofs and facades, linear green networks, and broader macro-GI strategies. …”
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Identification of novel serum lipid metabolism potential markers and metabolic pathways for oral cancer: a population-based study by Na Wang, Yujia Chen, Jianli Lin, Yulan Lin, Haoyuan Song, Weihai Huang, Liling Shen, Fa Chen, Fengqiong Liu, Jing Wang, Yu Qiu, Bin Shi, Ling Li, Lisong Lin, Lizhen Pan, Baochang He

“…The disease classification model, constructed using a KNN algorithm with 13 metabolites selected through LASSO screening, achieved the best performance, with an AUC of 0.978 (0.955-1.000). …”
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STOP-BANG: a Mandatory Tool for Targeted Respiratory Therapy in Bariatric Patients by R. D. Skvortsova, K. А. Аnisimova, K. А. Popova, V. А. Pavlova, А. N. Kulikov, D. I. Vasilevsky, S. G. Balandov, Z. А. Zaripova, А. А. Kazachenko, Yu. D. Rabik, T. S. Razumovskaya

“…Identification of patients with obstructive sleep apnea syndrome and high respiratory risk, optimization of the screening algorithm for these patients and administration of preventive non-invasive lung ventilation, makes it possible to prevent the development of perioperative complications, reduce duration of hospital stay and reduce mortality in patients undergoing surgery and bariatric surgery specifically.The objective: to evaluate the effectiveness of STOP-BANG questionnaire for preventive targeted respiratory therapy to reduce the risk of complications in bariatric patients. …”
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Weak fault diagnosis method for rolling bearings under strong background noise based on EEMD-FK-AMCKD by XIE Guizhong, XU Shuaiqiang, DU Wenliao, LUO Shuangqiang, LI Hao, WANG Liangwen, GONG Xiaoyun

“…ObjectiveTo address the challenge of accurately capturing weak features in vibration signals under strong noise interference, a joint filtering method combining ensemble empirical mode decomposition (EEMD), fast kurtogram (FK), and adaptive maximum correlation kurtosis deconvolution (AMCKD) was proposed.MethodsFirstly, the vibration signal was decomposed into multiple intrinsic mode functions (IMF) via EEMD for multiscale analysis. …”
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Maximizing YOLOv2 efficiency: A study on multiclass detection of indoor objects by G Divya Deepak, Subraya Krishna Bhat

“…The objective of the present study is to present a systematic approach for optimizing the key hyperparameters of YOLOv2 model for multiclass object detection, specifically targeting seven classes of indoor objects: chair, fire extinguisher, printer, screen, trash bin, exit, and clock. …”
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Toxoplasmosis seroprevalence in rheumatoid arthritis patients: A systematic review and meta-analysis. by Zahra Hosseininejad, Mehdi Sharif, Shahabeddin Sarvi, Afsaneh Amouei, Seyed Abdollah Hosseini, Tooran Nayeri Chegeni, Davood Anvari, Reza Saberi, Shaban Gohardehi, Azadeh Mizani, Mitra Sadeghi, Ahmad Daryani

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Exploring ischemic stroke based on the ferroptosis perspective: ECH1 may serve as a new biomarker and therapeutic target by Rendong Qu, Yiyan Zhang, Haojia Zhang, Ke Li, Boning Zhang, Hongxuan Tong, Tao Lu

“…Using differential expression analysis and machine learning algorithms, 12 potential hub genes were successfully screened. …”
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AI-Guided Delineation of Gross Tumor Volume for Body Tumors: A Systematic Review by Lea Marie Pehrson, Jens Petersen, Nathalie Sarup Panduro, Carsten Ammitzbøl Lauridsen, Jonathan Frederik Carlsen, Sune Darkner, Michael Bachmann Nielsen, Silvia Ingala

“…<b>Results</b>: After screening 2430 articles, 48 were included. The pooled diagnostic performance from the use of AI algorithms across different tumors and topological areas ranged 0.62–0.92 in dice similarity coefficient (DSC) and 1.33–47.10 mm in Hausdorff distance (HD). …”
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The use of heart rate variability, oxygen saturation, and anthropometric data with machine learning to predict the presence and severity of obstructive sleep apnea by Rafael Rodrigues dos Santos, Matheo Bellini Marumo, Alan Luiz Eckeli, Helio Cesar Salgado, Luiz Eduardo Virgílio Silva, Renato Tinós, Rubens Fazan

“…IntroductionObstructive sleep apnea (OSA) is a prevalent sleep disorder with a high rate of undiagnosed patients, primarily due to the complexity of its diagnosis made by polysomnography (PSG). Considering the severe comorbidities associated with OSA, especially in the cardiovascular system, the development of early screening tools for this disease is imperative. …”
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Prognostic Risk Signature and Comprehensive Analyses of Endoplasmic Reticulum Stress-Related Genes in Lung Adenocarcinoma by CaiZhen Yang, YuHui Wei, WenTao Li, JinMei Wei, GuoXing Chen, MingPeng Xu, GuangNan Liu

“…A total of 1034 samples from TCGA and GEO were used to screen differentially expressed genes. Further, Random Forest algorithm was utilized to screen characteristic genes related to prognosis. …”
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Machine learning based identification of anoikis related gene classification patterns and immunoinfiltration characteristics in diabetic nephropathy by Jing Zhang, Lulu Cheng, Shan Jiang, Duosheng Zhu

“…In addition, seven key genes, including PDK4, S100A8, HTRA1, CHI3L1, WT1, CDKN1B, and EGF, were screened by machine learning algorithm. Most of these genes exhibited low expression in renal tissue of DN patients and positive correlation with neutrophils, and their expressions were verified in an external dataset cell model. …”
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GPR65 is a novel immune biomarker and regulates the immune microenvironment in lung adenocarcinoma by Hanxu Zhou, Zhi Chen, Shuang Gao, Chaoqun Lian, Junjie Hu, Jin Lu, Lei Zhang

“…We screened differential genes (DEGs) in the immune and stromal components, and then screened modular genes by the WGCNA algorithm, which were intersected with DEGs and incorporated into the LASSO-COX regression model. …”
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Research on the Evaluation of the Node Cities of China Railway Express Based on Machine Learning by Chenglin Ma, Mengwei Zhou, Wenchao Kang, Haolong Wang, Jiajia Feng

“…The Random Forest model outperformed comparative algorithms with 99.5% prediction accuracy (8.33% higher than conventional classification models), particularly in handling multi-dimensional interactions between urban development factors. …”
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Identifying the NEAT1/miR-26b-5p/S100A2 axis as a regulator in Parkinson's disease based on the ferroptosis-related genes. by Taole Li, Jifeng Guo

“…According to the five machine algorithms, 4 features (S100A2, GNGT1, NEUROD4, FCN2) were screened and used to create a PD diagnostic model. …”
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Unveiling diagnostic biomarkers and therapeutic targets in lung adenocarcinoma using bioinformatics and experimental validation by Sixuan Wu, Yuanbin Tang, Qihong Pan, Yaqin Zheng, Yeru Tan, Junfan Pan, Yuehua Li

“…In addition, a machine learning model constructed based on Stepglm[backward] with the random forest algorithm achieved the highest C-index (0.999) and screened eight core genes, among which ST14 was noted for its excellent predictive ability. …”
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Smart driving assistance system for mining operations in foggy environments by Swades Kumar Chaulya, Monika Choudhary, Naresh Kumar, Vikash Kumar, Abhishek Chowdhury

“…Finally, the screen fitted in the dashboard is forward-facing to the operator's seat and displays the final output. …”
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