Identification and validation of the nicotine metabolism-related signature of bladder cancer by bioinformatics and machine learning by Yating Zhan, Min Weng, Yangyang Guo, Dingfeng Lv, Feng Zhao, Zejun Yan, Junhui Jiang, Yanyi Xiao, Lili Yao

“…Integrative machine learning combination based on 10 machine learning algorithms was used for the construction of robust signature. …”
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Bioinformatic identification of signature miRNAs associated with fetoplacental vascular dysfunction in gestational diabetes mellitus by Yulan Lu, Chunhong Liu, Xiaoxia Pang, Xinghong Chen, Chunfang Wang, Huatuo Huang

“…Firstly, differentially expressed miRNA genes (DEMGs) were evaluated using limma package. …”
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Copper Metabolism-Related Genes as Biomarkers in Colon Adenoma and Cancer by Zhang T, Fu Y

“…Five machine-learning algorithms were employed to identify biomarkers. The degree of immune infiltration was evaluated using single-sample Gene Set Enrichment Analysis (ssGSEA), and the expression profiles of these biomarkers across various cell types were further characterized using single-cell RNA sequencing (scRNA-seq). …”
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Thyroid nodule classification in ultrasound imaging using deep transfer learning by Yan Xu, Mingmin Xu, Zhe Geng, Jie Liu, Bin Meng

“…In this study, we investigate the predictive efficacy of distinguishing between benign and malignant thyroid nodules by employing traditional machine learning algorithms and a deep transfer learning model, aiming to advance the diagnostic paradigm in this field. …”
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Enhancing Sustainable Manufacturing in Industry 4.0: A Zero-Defect Approach Leveraging Effective Dynamic Quality Factors by Rouhollah Khakpour, Ahmad Ebrahimi, Seyed Mohammad Seyed Hosseini

“…In addition to eliminating waste in manufacturing resources, it also evaluates the impact of these improvements on sustainability. …”
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The role of mitochondria-related genes in hepatocellular carcinoma prognosis: construction of prognostic models based on machine learning by Fei Gao, Fei Teng, Yuxiang Wan, Qiaoli Zhang, Jinchang Huang

“…Weighted gene co-expression network analysis was subsequently employed to construct co-expression networks and identify key modules associated with HCC progression. We evaluated 113 machine learning algorithms to develop mitochondrial gene-based prognostic models. …”
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Radiological Assessment of Charcot Neuro-Osteoarthropathy in Diabetic Foot: A Narrative Review by Antonio Mascio, Chiara Comisi, Virginia Cinelli, Dario Pitocco, Tommaso Greco, Giulio Maccauro, Carlo Perisano

“…Nuclear imaging, including bone scintigraphy, radiolabeled leukocyte scans, and FDG-PET/CT, offers additional diagnostic precision in complex cases, especially when differentiating CNO from infections or evaluating patients with metal implants. …”
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Enhanced Homomorphic Encryption for Cloud Security Through Individual Optimization by Radha Marepalli, Sunitha Vanamala, Manoj Kumar Konda, Venkata Rama Lakshmi Gundala, Prasanthi B.

“…These algorithms are also often referred to as PSO strategies. …”
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An efficient retrieval method on Google Earth Engine and comparison with hybrid methods: a case study of leaf area index retrieval by Sijia Li, Zhiguang Tang, Kaisen Ma, Zhenyi Wang, Wenjuan Li

“…However, these algorithms cannot quantify the uncertainty of estimates. …”
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Identification of potential metabolic biomarkers and immune cell infiltration for metabolic associated steatohepatitis by bioinformatics analysis and machine learning by Haoran Xie, Junjun Wang, Qiuyan Zhao

“…Methods: This study extracted multiple datasets from the GEO database to identify metabolism-related differentially expressed genes (MRDEGs). Protein-Protein Interaction (PPI) network and machine learning algorithms, including Least Absolute Shrinkage and Selection Operator (LASSO) regression, Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and Random Forest (RF), were applied to screen for signature MRDEGs. …”
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FAR1 as a ferroptosis-related biomarker and potential therapeutic target in acute kidney injury: integrated bioinformatics and experimental validation by Hao Duan, Jie Yan, Xingyu Fan, Yijun Du, Xing Zhong, Tianrong Pan, Yue Wang

“…Eight diagnostic biomarkers were selected using multiple algorithms, and their predictive accuracy was validated through ROC curve analysis. …”
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Exploring fecal microbiota signatures associated with immune response and antibiotic impact in NSCLC: insights from metagenomic and machine learning approaches by Wenjie Han, Wenjie Han, Yuhang Zhou, Yuhang Zhou, Yiwen Wang, Yiwen Wang, Xiaolin Liu, Tao Sun, Tao Sun, Junnan Xu, Junnan Xu, Junnan Xu

“…Among eight machine learning algorithms evaluated, the optimal model was selected to construct a predictive framework for immunotherapy response.ResultsMicrobial α-diversity was significantly elevated in responders compared to non-responders, with antibiotic administration further amplifying this difference—most notably at the species level. …”
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Analysis and validation of hub genes for atherosclerosis and AIDS and immune infiltration characteristics based on bioinformatics and machine learning by Qirui Zheng, Yupeng Wu, Xiaojiao Zhang, Yuzhu Zhang, Zaihan Zhu, Bo Luan, Peizhuo Zang, Dandan Sun

“…Hub genes were filtered using topological and machine learning algorithms and validated in external cohorts. Then immune infiltration and correlation analysis of hub genes were constructed. …”
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The 2024 revised clinical guidelines on the management of thyroid tumors by the Japan Association of Endocrine Surgery by Iwao Sugitani, Naomi Kiyota, Yasuhiro Ito, Naoyoshi Onoda, Tomo Hiromasa, Kiyomi Horiuchi, Seigo Kinuya, Tetsuo Kondo, Sueyoshi Moritani, Kiminori Sugino, Hisato Hara

“…Following a comprehensive search of the literature and systematic review to evaluate the overall evidence, we aimed to present optimal recommendations by considering the balance of benefits and harms from the patient’s perspective. …”
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An IoT-Enabled Wearable Device for Fetal Movement Detection Using Accelerometer and Gyroscope Sensors by Atcharawan Rattanasak, Talit Jumphoo, Wongsathon Pathonsuwan, Kasidit Kokkhunthod, Khwanjit Orkweha, Khomdet Phapatanaburi, Pattama Tongdee, Porntip Nimkuntod, Monthippa Uthansakul, Peerapong Uthansakul

“…Data were collected from 35 pregnant women at Suranaree University of Technology (SUT) Hospital. This study evaluated ten signal extraction methods, six machine learning algorithms, and four feature selection techniques to enhance classification performance. …”
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Resolving multi-image spatial lipidomic responses to inhaled toxicants by machine learning by Nathanial C. Stevens, Tong Shen, Joshua Martinez, Veneese J. B. Evans, Morgan C. Domanico, Elizabeth K. Neumann, Laura S. Van Winkle, Oliver Fiehn

“…Abstract Regional responses to inhaled toxicants are essential to understand the pathogenesis of lung disease under exposure to air pollution. We evaluate the effect of combined allergen sensitization and ozone exposure on eliciting spatial differences in lipid distribution in the mouse lung that may contribute to ozone-induced exacerbations in asthma. …”
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Associations between organophosphorus pesticides exposure and age-related macular degeneration risk in U.S. adults: analysis from interpretable machine learning approaches by Yu-Xin Jiang, Si-Yu Gui, Xiao-Dong Sun

“…CONCLUSION: Urinary DAP metabolites of OPPs exposure are associated with AMD risk and ML algorithms show the excellent generalizability and differentiability in the course of AMD risk prediction.…”
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A Pilot Study on Mixed-Reality Approaches for Detecting Upper-Limb Dysfunction in Multiple Sclerosis: Insights on Cerebellar Tremor by Etty Sabatino, Miriam Moschetta, Andrea Lucaroni, Giacinto Barresi, Carlo Ferraresi, Jessica Podda, Erica Grange, Giampaolo Brichetto, Anna Bucchieri

“…Data from twelve healthy individuals served as benchmarks, while nine PwMS, including three with cerebellar tremor and one with ataxia, were tested to evaluate the tool’s diagnostic potential. Clustering algorithms applied to the kinematic data classified participants into distinct groups, showing that PwMS without cerebellar symptoms sometimes displayed behavior similar to healthy controls. …”
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Classification of Individuals With COVID-19 and Post–COVID-19 Condition and Healthy Controls Using Heart Rate Variability: Machine Learning Study With a Near–Real-Time Monitoring C... by Carlos Alberto Sanches, Andre Felipe Henriques Librantz, Luciana Maria Malosá Sampaio, Peterson Adriano Belan

“…Classification models were developed using supervised machine learning algorithms (decision tree, support vector machines, k-nearest neighbor, and neural networks) and evaluated through cross-validation. …”
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A computer-based method for the automatic identification of the dimensional features of human cervical vertebrae by Nicola Cappetti, Luca Di Angelo, Carlotta Fontana, Antonio Marzola

“…The manual method demonstrated poor repeatability and reproducibility, with substantial differences between the minimum and maximum values for the measured features in intra- and inter-operator evaluations. …”
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