Machine learning approaches reveal methylation signatures associated with pediatric acute myeloid leukemia recurrence by Yushuang Dong, HuiPing Liao, Feiming Huang, YuSheng Bao, Wei Guo, Zhen Tan

“…DNA methylation data from 696 newly diagnosed and 194 relapsed pediatric AML patients were analyzed. Feature selection algorithms, including Boruta, least absolute shrinkage and selection operator, light gradient boosting machine, and Monte Carlo feature selection, were employed to screen and rank methylation sites strongly correlated with AML recurrence. …”
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Identification of metabolic biomarkers in idiopathic pulmonary arterial hypertension using targeted metabolomics and bioinformatics analysis by Chuang Yang, Yi-Hang Liu, Hai-Kuo Zheng

“…This study used metabolomics, machine learning algorithms and bioinformatics to screen for potential metabolic biomarkers associated with the diagnosis of PAH. …”
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Intelligent design and synthesis of energy catalytic materials by Linkai Han, Zhonghua Xiang

“…We summarize the sources of data collection, the intelligent algorithms commonly used to build ML models, and the laboratory modules for the intelligent synthesis of materials. …”
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Artificial Intelligence in Pediatric Orthopedics: A Comprehensive Review by Andrea Vescio, Gianluca Testa, Marco Sapienza, Filippo Familiari, Michele Mercurio, Giorgio Gasparini, Sergio de Salvatore, Fabrizio Donati, Federico Canavese, Vito Pavone

“…Eligible articles were screened and categorized based on application domains, AI models used, datasets, and reported outcomes. …”
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Comprehensive profiling of chemokine and NETosis-associated genes in sarcopenia: construction of a machine learning-based diagnostic nomogram by Yingwei Wang, Le Wang, Yan Zhang, Minghui Wang, Huaying Zhao, Cheng Huang, Huaiyang Cai, Shuangyang Mo

“…Two machine learning algorithms and univariate analysis were integrated to screen signature genes, which were subsequently used to construct diagnostic nomogram models for sarcopenia. …”
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Mapping Vegetation Dynamics in Wyoming: A Multi-Temporal Analysis using Landsat NDVI and Clustering by N. Kuppala, C. Navneet Krishna, V. V. Sajith Variyar, R. Sivanpillai

“…NDVI data were screened for outliers using the interquartile range method. …”
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Geographic origin discrimination and quantification of phenolic compounds and moisture in Artemisia argyi folium using NIRS and chemometrics by Lifei Hu, Yifan Wang, Xin Wu, Yuanyuan Shan, Fengxiao Zhu, Fan Zhang, Qiang Yang, Mingxing Liu

“…Partial least squares regression (PLSR) models for 17 phenolic components and moisture content were screened using different preprocessing methods, identifying three parameters suitable for rapid quantification: eupatilin, jaceosidin, and moisture. …”
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DETERMINATION OF THE BASIC PARAMETERS OF SENSOR DEVICES FOR THE IMPLEMENTATION OF PSYCHONEUROLOGICAL RESEARCH WITH THE INTRODUCTION OF MULTITOUCH TECHNOLOGY by Karina Selivanova, Oleg Avrunin, Nikita Kazimirov

“…The methods of computer modeling and visualization of dynamic tests using the multi-platform programming language Python were used. …”
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GALNT6 associated with O-GlcNAcylation contributes to the tumorigenesis of oral squamous cell carcinoma by Junfeng Yan, Xuan Tang, Yingying Zhou, Xin Xiong

“…O-GlcNAcylation related genes with differential expression were screened and filtered by LASSO, RF and SVM machine learning models. …”
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The role of artificial intelligence in occupational health in radiation exposure: a scoping review of the literature by Zohreh Fazli, Mehran Sadeghi, Mohebat Vali, Parvin Ahmadinejad

“…After removing duplicate references, screened based on title, keywords, and abstract, Ultimately, 59 eligible articles were selected, which utilized various artificial intelligence tools, such as expert systems, machine learning, deep learning, and other applied AI models. …”
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Exposure patterns and the risk factors of Crimean Congo hemorrhagic fever virus amongst humans, livestock and selected wild animals at the human/livestock/wildlife interface in Isi... by Eugine Mukhaye, James M Akoko, Richard Nyamota, Athman Mwatondo, Mathew Muturi, Daniel Nthiwa, Lynn J Kirwa, Joel L Bargul, Hussein M Abkallo, Bernard Bett

“…Serum samples from all recruited humans and animals were collected and screened for CCHFV antibodies using ID Screen multispecies, double-antigen IgG enzyme-linked immunosorbent assay (ELISA). …”
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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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IKZF1 as a potential therapeutic target for dendritic cell-mediated immunotherapy in IgA nephropathy by Fei Peng, Chunjia Sheng, Jiayi He, Yena Zhou, Yilun Qu, Shuwei Duan, Yinghua Zhao, Jikai Xia, Jie Wu, Guangyan Cai, Lingling Wu, Chuyue Zhang, Xiangmei Chen

“…Receiver operating characteristic (ROC) curve analysis and machine learning algorithms were employed to screen for DC-related diagnostic biomarkers from the dataset. …”
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Integrated Single-Cell and Spatial Transcriptomic Analysis Identifies ISR-Related Genes Driving Immune Regulation in Parkinson’s Disease by Jiang H, Zhang X, Feng S, Feng W

“…ISR scores were compared across brain cell types, and differentially expressed genes in microglia were further screened using Lasso regression and random forest algorithms. …”
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Comprehensive bioinformatics analysis of the common mechanism of atherosclerosis and atrial fibrillation: emphasizing mitochondrial metabolic disorder and immune inflammation by Rui Dai, Xiaotong Lei, Xiaojun Liu, Chen Bian

“…Three machine learning algorithms (LASSO, SVM, and random forest) were applied to screen hub genes, followed by validation in independent datasets. …”
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Software and Hardware Control System for Implementing the Balance Error Scoring System by Oksana Blavt, Gennadii Iedynak, Lesia Galamanzhuk, Tetyana Helzhynska, Yurii Kachurak, Yulia Mykhalskа, Liubov Levandovska, Rostyslav Tymkovych

“…For real-time data transmission to the PC screen and smartphone, wireless modules HC-05 (Bluetooth) or ESP32 (Wi-Fi) were used. …”
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Sodium Propionate Alleviates Atopic Dermatitis by Inhibiting Ferroptosis via Activation of LTBP2/FABP4 Signaling Pathway by Xie A, Li W, Ye D, Yin Y, Wang R, Wang M, Yu R

“…Analysis using three algorithms identified potential therapeutic targets of SP. …”
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Experimental validation of cuproptosis-associated molecular signatures and their immunological implications in pulmonary tuberculosis by Xiaofang Liu, Xiaofang Liu, Qianqian Ma, Zhiming Li, Yong Xue, Jie Mi, Yuxi Li, Chunfeng Bai, Donglin Guo, Yinping Liu, Yan Liang, Jianqin Liang, Xueqiong Wu

“…Subsequent analyses included functional enrichment, gene interaction, and protein-protein interaction (PPI) network construction. Hub CRGs were screened out via least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) algorithms. …”
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Diagnosis methods for pancreatic cancer with the technique of deep learning: a review and a meta-analysis by Yuanbo Bi, Dongrui Li, Ruochen Pang, Chengxv Du, Da Li, Xiaoyv Zhao, Haitao Lv

“…Inclusion criteria were studies involving PDAC patients, using deep learning algorithms for diagnosis evaluation, using histopathological results as the reference standard, and having sufficient data. …”
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Combined assessment of stress hyperglycemia ratio and glycemic variability to predict all-cause mortality in critically ill patients with atherosclerotic cardiovascular diseases ac... by Fuxu Wang, Yu Guo, Yuru Tang, Shuangmei Zhao, Kaige Xuan, Zhi Mao, Ruogu Lu, Rongyao Hou, Xiaoyan Zhu

“…Five ML algorithms were employed for mortality risk prediction, with SHapley Additive exPlanations (SHAP) applied to identify critical predictors. …”
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