Deciphering the role of metal ion transport-related genes in T2D pathogenesis and immune cell infiltration via scRNA-seq and machine learning by Zuhui Pu, Zuhui Pu, Tony Bowei Wang, Ying Lu, Ying Lu, Zijing Wu, Zijing Wu, Yuxian Chen, Ziqi Luo, Xinyu Wang, Lisha Mou, Lisha Mou

“…We employed 12 machine learning algorithms to develop predictive models and assessed immune cell infiltration using single-sample gene set enrichment analysis (ssGSEA). …”
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Interpretable machine learning model for early prediction of disseminated intravascular coagulation in critically ill children by Jintuo Zhou, Yongjin Xie, Ying Liu, Peiguang Niu, Huajiao Chen, Xiaoping Zeng, Jinhua Zhang

“…Six machine learning algorithms—logistic regression (LR), extreme gradient boosting (XGB), random forest (RF), support vector machine (SVM), decision tree (DT), and k-nearest neighbor (KNN)—were employed to construct predictive models for DIC in critically ill children. …”
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Integrative analysis of crotonylation-associated genes reveals prognostic and therapeutic targets in gliomas by Bowen Yin, Bowen Yin, Zhuoyang Fan, Panpan Yu, Panpan Yu, Jin Li, Jin Li, Yilin Wang, Yilin Wang, Minfeng Shu, Minfeng Shu

“…A prognostic risk score was developed using machine learning algorithms and validated in multiple cohorts. Genomic alterations, immune landscapes, and therapeutic responses were examined in relation to the risk score. …”
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Correlation between the white blood cell/platelet ratio and 28-day all-cause mortality in cardiac arrest patients: a retrospective cohort study based on machine learning by Huai Huang, Guangqin Ren, Shanghui Sun, Zhi Li, Yongtian Zheng, Lijuan Dong, Shaoliang Zhu, Xiaosheng Zhu, Wenyu Jiang

“…ObjectiveThis study aims to evaluate the association between the white blood cell-to-platelet ratio (WPR) and 28-day all-cause mortality among patients experiencing cardiac arrest.MethodsUtilizing data from 748 cardiac arrest patients in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) 2.2 database, machine learning algorithms, including the Boruta feature selection method, random forest modeling, and SHAP value analysis, were applied to identify significant prognostic biomarkers. …”
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Deep learning informed multimodal fusion of radiology and pathology to predict outcomes in HPV-associated oropharyngeal squamous cell carcinomaResearch in context by Bolin Song, Amaury Leroy, Kailin Yang, Tanmoy Dam, Xiangxue Wang, Himanshu Maurya, Tilak Pathak, Jonathan Lee, Sarah Stock, Xiao T. Li, Pingfu Fu, Cheng Lu, Paula Toro, Deborah J. Chute, Shlomo Koyfman, Nabil F. Saba, Mihir R. Patel, Anant Madabhushi

“…Interpretation: Our findings underscore the potential of multimodal deep learning in accurately stratifying OPSCC risk, informing tailored treatment strategies and potentially refining existing treatment algorithms. Funding: The National Institutes of Health, the U.S. …”
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Leveraging Machine Learning and Remote Sensing for Water Quality Analysis in Lake Ranco, Southern Chile by Lien Rodríguez-López, Lisandra Bravo Alvarez, Iongel Duran-Llacer, David E. Ruíz-Guirola, Samuel Montejo-Sánchez, Rebeca Martínez-Retureta, Ernesto López-Morales, Luc Bourrel, Frédéric Frappart, Roberto Urrutia

“…The successful application of machine learning algorithms emphasizes their potential to elucidate the dynamics of algal biomass in Lake Ranco, located in the southern region of Chile. …”
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Stage actor tracking method based on infrared ink marking(基于红外油墨标记的舞台演员跟踪算法) by 李平(LI Ping), 陈书界(CHEN Shujie), 王登辉(WANG Denghui), 刘钟淋(LIU Zhonglin), 王勋(WANG Xun), 周迪(ZHOU Di), 丁勇(DING Yong)

“…When well illuminated, the state-of-the-art multi-object tracking algorithms can reach real-time and stable tracking results. …”
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Development and validation of an early diagnosis model for severe mycoplasma pneumonia in children based on interpretable machine learning by Si Xie, Mo Wu, Yu Shang, Wenbin Tuo, Jun Wang, Qinzhen Cai, Chunhui Yuan, Cong Yao, Yun Xiang

“…Clinical data were selected through Lasso regression analysis, followed by the application of eight machine learning algorithms to develop early warning model. The accuracy of the model was assessed using validation and prospective cohort. …”
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Collaborative management of water-agriculture-energy-ecology nexus for increasing carbon sequestration to sustainable development: A case study in inland river Northwest China by Xiaoyu Tang, Yue Huang, Xiaohui Pan, Yunan Ling, Chanjuan Zan, Jiabin Peng, Xi Chen, Tie Liu

“…This study proposes a WAEE nexus co-optimization model based on mixed-coding multi-objective evolutionary algorithms (EMCMO). The model incorporates multiple objectives and constraints into its framework, encompassing agricultural economic efficiency optimization, cascade reservoir hydropower production, carbon sequestration through agricultural practices, and ecological security as a key constraint. …”
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Trends in management of odontoid fractures 2010–2021 by Michael J. Gouzoulis, BS, Anthony E. Seddio, BS, Albert Rancu, BS, Sahir S. Jabbouri, MD, Jay Moran, MD, Arya Varthi, MD, Daniel R. Rubio, MD, Jonathan N. Grauer, MD

“…While these decisions were predicted by some clinical factors, both also correlated with nonclinical factors suggesting room for more consistent algorithms.…”
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Open-Source Data Logger System for Real-Time Monitoring and Fault Detection in Bench Testing by Marcio Luís Munhoz Amorim, Jorge Gomes Lima, Norah Nadia Sánchez Torres, Jose A. Afonso, Sérgio F. Lopes, João P. P. do Carmo, Lucas Vinicius Hartmann, Cicero Rocha Souto, Fabiano Salvadori, Oswaldo Hideo Ando Junior

“…Initial laboratory tests validate its feasibility for real-time data acquisition and highlight its potential for creating datasets to support advanced diagnostic algorithms. Future work will focus on enhancing telemetry capabilities, improving Wi-Fi and cloud integration, and developing machine learning-based diagnostic methodologies for combustion and electric engines.…”
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Integrative multi-omics analysis reveals the interaction mechanisms between gut microbiota metabolites and ferroptosis in rheumatoid arthritis by Lifang Liang, Lifang Liang, Lifang Liang, Huaguo Liang, Min He, Min He, Min He, Huiling Zhang, Huiling Zhang, Huiling Zhang, Peifeng Ke, Peifeng Ke, Peifeng Ke

“…To systematically investigate the regulatory relationship between key ferroptosis genes and gut metabolites in RA, this study employed an integrative multi-omics approach combined with machine learning algorithms and single-cell transcriptomic data, identifying and validating GPX3 and MYC as potential critical ferroptosis regulators in RA.Methods and resultsFirst, 16 candidate genes were obtained by intersecting WGCNA, differential expression analysis results, and targets related to ferroptosis and gut microbiota. …”
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FGFR2 identified as a NETs-associated biomarker and therapeutic target in diabetic foot ulcers by Linrui Dai, Shunli Rui, Mengling Yang, Shiyan Yu, Qingqing Chen, Hongyan Wang, Bo Deng, Liling Deng, Wei Hao, Xiaohua Wu, David G. Armstrong, Zhidong Cao, Xiaodong Duan, Wuquan Deng

“…LASSO logistic regression and Random Forest algorithms were applied to the NETDEGs to select key feature genes. …”
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Integrating ultrasound radiomics and clinicopathological features for machine learning-based survival prediction in patients with nonmetastatic triple-negative breast cancer by Wenwen, Zekun Jiang, Jingyan Liu, Dingbang Liu, Yiyue Li, Yushuang He, Haina Zhao, Lin Ma, Yixin Zhu, Qiongxian Long, Jun Gao, Honghao Luo, Heng Jiang, Kang Li, Xiaorong Zhong, Yulan Peng

“…A thorough chart review was conducted for each patient to collect clinicopathological and sonographic features, and ultrasound radiomics features were obtained by PyRadiomics. Deep learning algorithms were utilized to delineate ROIs on ultrasound images. …”
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In-Silico discovery of novel cephalosporin antibiotic conformers via ligand-based pharmacophore modelling and de novo molecular design by Rayhan Chowdhury, Samia Akter Saima, Md. Al Amin, Md. Kawsar Habib, Ramisa Binti Mohiuddin, Ali Mohamod Wasaf Hasan, Roksana Khanam, Shahin Mahmud

“…These candidates were then fused with the cephalosporin core using genetic algorithms and fragment-based design, resulting in 30 novel synthetic models. …”
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A Next-generation Exoplanet Atmospheric Retrieval Framework for Transmission Spectroscopy (NEXOTRANS): Comparative Characterization for WASP-39 b Using JWST NIRISS, NIRSpec PRISM,... by Tonmoy Deka, Tasneem Basra Khan, Swastik Dewan, Priyankush Ghosh, Debayan Das, Liton Majumdar

“…We present NEXOTRANS , an atmospheric retrieval framework that integrates Bayesian inference using UltraNest / PyMultiNest with four machine learning algorithms: Random Forest , Gradient Boosting , K-Nearest Neighbor , and Stacking Regressor . …”
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Deep-Learning-Based Computer-Aided Grading of Cervical Spinal Stenosis from MR Images: Accuracy and Clinical Alignment by Zhiling Wang, Xinquan Chen, Bin Liu, Jinjin Hai, Kai Qiao, Zhen Yuan, Lianjun Yang, Bin Yan, Zhihai Su, Hai Lu

“…<b>Objective:</b> This study aims to apply different deep learning convolutional neural network algorithms to assess the grading of cervical spinal stenosis and to evaluate their consistency with clinician grading results as well as clinical manifestations of patients. …”
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Machine learning–guided single-cell multiomics uncovers GDF15-driven immunosuppressive niches in NSCLC: A translational framework for overcoming anti-PD-1 resistance by Xianfei Zhang, Zhengxin Yin, Xueyu Chen, Nengchong Zhang, Shengjia Yu, Congcong Zhu, Lianggang Zhu, Liulan Shao, Bin Li, Runsen Jin, Hecheng Li

“…Comparative evaluation of 22 survival algorithms across four NSCLC cohorts (n=156) led to the development of an Accelerated Oblique Random Survival Forest model, which outperformed conventional Cox regression and deep learning methods in predictive accuracy (training C-index=0.864; test C-index=0.748). …”
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A new signature associated with anoikis predicts the outcome and immune infiltration in nasopharyngeal carcinoma by Yonglin Luo, Wenyang Wei, Yaxuan Huang, Jun Li, Weiling Qin, Quanxiang Hao, Jiemei Ye, Zhe Zhang, Yushan Liang, Xue Xiao, Yonglin Cai

“…Results Three differentially expressed ARGs (CDC25C, E2F1 and RBL2) with prognostic value were identified by the intersection of multiple machine learning algorithms. A risk score based on t 3-ARG feature was developed to stratify NPC patients into two distinct risk groups using the optimal model, Random Survival Forest. …”
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Ocular markers of microangiopathy and their possible association with cardiovascular risk in patients with systemic inflammatory rheumatic diseases: a systematic review by Bengta Sturm, Anna-Lena Zang, Julia Stingl, Rebecca Hasseli-Fräbel, Antonis Fanouriakis, Andreas Schwarting, Andreas Schwarting, Christian Geber, Julia Weinmann-Menke, Mohammed Alhaddad, Konstantinos Triantafyllias, Konstantinos Triantafyllias

“…To date, there is limited data on the optimal CV screening methods for individuals with ARDs, as conventional risk algorithms may underestimate the influence of chronic inflammation. …”
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