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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Intratumoral Heterogeneity Scores as Predictors of Invasiveness in Lung Adenocarcinoma Presenting as Pure Ground-Glass Nodules: Insights from Explainable Machine Learning-Based Ter... by Wang Peng BS, Wanyin Qi BS, Yunhua Li BS, Sanhong Zhang BS, Juan Long BS

“…Introduction Preoperative differentiation of adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) using computed tomography (CT) is crucial for clinical management. …”
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Integrated multi-omics analysis and predictive modeling of heart failure using sepsis-related gene signature. by Yiping Lang, Tianyu Liang, Fei Li

“…<h4>Methods</h4>Three sepsis-related datasets (GSE65682, GSE54514, and GSE95233) were analyzed to identify differentially expressed genes (DEGs) following batch effect correction using the ComBat algorithm. …”
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COMPARATIVE CHARACTERISTICS OF BIOMATERIALS FOR THE REPLACEMENT OF JAW BONE DEFECTS AND THEIR ROLE IN THE PREVENTION OF INFLAMMATORY COMPLICATIONS by V.M. Havryliev, A.V. Kopchak, N.B. Kuzniak, D.V. Steblovski, O.A. Toropov, P.I. Yatsenko

“…The functional characteristics of osteoconductive scaffolds, their microand nanostructural properties, and biomimetic features were evaluated. Based on the obtained data, we developed an algorithm for the selection and application of biomaterials in oral surgery: precise selection of the type of bone substitute based on the anatomical and functional characteristics of the defect; individualized implant preparation, including surface modification; and the use of bioactive matrices containing growth factors and structural analogues of the extracellular matrix. …”
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Goal-directed hemodynamic therapy in patients with colorectal cancer undergoing laparoscopic surgery by V. A. Panafidina, I. V. Shlyk

“…To estimate the efficacy of a modified algorithm of goal-directed hemodynamic management in patients with colorectal cancer who undergo laparoscopic surgery based on non-invasive monitoring of cardiac output.Subjects and methods. …”
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Comprehensive bioinformatics analysis uncover molecular pathways shared between osteoarthritis and atherosclerosis by Yingchao Jin, Hua Zhang

“…In addition, the immune infiltration of OA and AS was analyzed and compared based on the ssGSEA algorithm, and the correlation between hub genes and infiltrating immune cells was evaluated in OA and AS, respectively. …”
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Integrative analysis identifies IL-6/JUN/MMP-9 pathway destroyed blood-brain-barrier in autism mice via machine learning and bioinformatic analysis by Cong Hu, Heli Li, Jinru Cui, Yunjie Li, Feiyan Zhang, Hao Li, Xiaoping Luo, Yan Hao

“…This study aimed to identify critical genes linking BBB function and neuroinflammatory activation, with the ultimate goal of evaluating potential therapeutic targets. Through integrative analysis combining differential gene expression profiling with three machine learning algorithms - Least Absolute Shrinkage and Selection Operator (LASSO) regression, Support Vector Machine Recursive Feature Elimination (SVM-RFE), and RandomForest combined with eXtreme Gradient Boosting (XGBoost) - we identified four hub genes, with JUN emerging as a core regulator. …”
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Impacts of Spatial Expansion of Urban and Rural Construction on Typhoon-Directed Economic Losses: Should Land Use Data Be Included in the Assessment? by Siyi Zhou, Zikai Zhao, Jiayue Hu, Fengbao Liu, Kunyuan Zheng

“…Meanwhile, existing studies often overlook the complex relationship between the spatial expansion of urban and rural construction (SEURC) and typhoon disaster losses, particularly their differential manifestations across different regions and disaster intensities. …”
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Non-invasive urinary proteomic biomarkers for prognostic assessment in sepsis by Qingbo Zeng, Nianqing Zhang, Junjie Zeng, Lincui Zhong, Qingwei Lin, Longping He, Xiaomin Song, Jingchun Song

“…Feature variables were selected from the differentially expressed proteins using the Least Absolute Shrinkage and Selection Operator (LASSO) and the random forest algorithms and by determining whether their proteins had an area under the curve (AUC) greater than 0.8. …”
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Identification of a Prognosis-Related Risk Signature for Bladder Cancer to Predict Survival and Immune Landscapes by Linhui Wang, Yutao Wang, Jianfeng Wang, Luanfeng Li, Jianbin Bi

“…The Kaplan–Meier survival curves and receiver operating characteristics were used to evaluate the model’s effectiveness. The potential biological functions of the selected genes were analyzed using CIBERSORT and ESTIMATE algorithms. …”
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Multi-modality radiomics diagnosis of breast cancer based on MRI, ultrasound and mammography by Jiao Wu, YongXin Li, Wanqing Gong, Qian Li, Xue Han, Tingting Zhang

“…Abstract Objective To develop a multi-modality machine learning-based radiomics model utilizing Magnetic Resonance Imaging (MRI), Ultrasound (US), and Mammography (MMG) for the differentiation of benign and malignant breast nodules. …”
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An integrated machine learning framework for developing and validating diagnostic models and drug predictions based on ulcerative colitis genes by Na An, Zhongwen Lu, Yang Li, Bing Yang, Shaozhen Ji, Xu Dong, Zhaoliang Ding

“…Next, we identified differentially expressed genes (DEGs) that are associated with UC. …”
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Multi‐Omic Analysis Reveals a Lipid Metabolism Gene Signature and Predicts Prognosis and Chemotherapy Response in Thyroid Carcinoma by Yuqin Tu, Yanchen Chen, Linlong Mo, Guiling Yan, Jingling Xie, Xinyao Ji, Shu Chen, Changchun Niu, Pu Liao

“…The immune landscape was evaluated using the CIBERSORT algorithm, and chemotherapeutic response was predicted utilizing the “pRRophetic” R package. …”
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Identification and validation of aging related genes in osteoarthritis by Jian Du, Jian Du, Tian Zhou, Yanghui Dong, Yunchao Sun, Wei Peng

“…This study explores the relationship between aging related genes (ARGs) and OA, providing potential new targets for understanding the pathogenesis and treatment of OA.MethodsThe OA synovial tissue dataset was obtained from the GEO database, and differentially expressed genes (DEGs) were screened. The DEGs were intersected with ARGs to identify differentially expressed aging related genes (DEARGs), which were then subjected to functional enrichment analysis, PPI network analysis, and machine learning algorithms (LASSO and RF) to identify key genes. …”
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On the electron agyrotropy during rapid asymmetric magnetic island coalescence in presence of a guide field by E. Cazzola, M. E. Innocenti, M. V. Goldman, D. L. Newman, S. Markidis, G. Lapenta

“…We study the departure from isotropic and gyrotropic behavior by means of different robust detection algorithms proposed in the literature. …”
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Robust Vessel Segmentation in Fundus Images by A. Budai, R. Bock, A. Maier, J. Hornegger, G. Michelson

“…The proposed method is evaluated using the STARE and DRIVE databases and we propose a new high resolution fundus database to compare it to the state-of-the-art algorithms. …”
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A CT-based machine learning model for using clinical-radiomics to predict malignant cerebral edema after stroke: a two-center study by Lingfeng Zhang, Gang Xie, Yue Zhang, Yue Zhang, Junlin Li, Junlin Li, Wuli Tang, Wuli Tang, Ling Yang, Ling Yang, Kang Li

“…Ultimately, the efficacy of these models was evaluated by measuring the operating characteristics of the subjects through their area under the curve (AUCs).ResultsLogistic regression (LR) was found to be the most effective machine learning algorithm, for forecasting the MCE. …”
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Bioinformatics&amp;#x2011;Based Analysis Reveals Diagnostic Biomarkers and Immune Landscape in Atopic Dermatitis by Yang M, Zhang X, Zhou C, Du Y, Zhou M, Zhang W

“…Least Absolute Shrinkage and Selection Operator (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE) algorithms were used to screen hub genes. Immune cell infiltration was evaluated using CIBERSORT. …”
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Exploration of Epigenetic Mechanisms and Biomarkers Among Patients with Very-Late-Onset Schizophrenia-Like Psychosis by Gan Y, Yue W, Sun J, Yang D, Fang C, Zhou Z, Yin J, Zhou H

“…We prioritized key methylation sites through integrated analysis of methylation quantitative trait loci (meQTL), linkage disequilibrium (LD) patterns, and blood-brain methylation correlations. Machine learning algorithms generated diagnostic models, with classification performance evaluated using Area Under the Curve (AUC) metrics.Results: Analysis revealed distinct DNA methylation signatures in VLOSLP patients compared to controls. …”
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Integrated network toxicology and bioinformatics reveal PFAS-driven prognostic biomarkers and molecular mechanisms in breast cancer: insights from transcriptome analysis and molecu... by Yingqiang Fu, Yiyang Liu, Ziqi Sui

“…Enrichment analysis, network construction, and survival analysis were performed to elucidate the biological mechanisms and prognostic value. The CIBERSORT algorithm assessed immune cell infiltration, and molecular docking evaluated interactions between PFAS compounds and key genes. …”
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