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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Do We Need to Add the Type of Treatment Planning System, Dose Calculation Grid Size, and CT Density Curve to Predictive Models? by Reza Reiazi, Surendra Prajapati, Leonardo Che Fru, Dongyeon Lee, Mohammad Salehpour

“…<b>Methods:</b> This study evaluated dose calculation differences in the head and neck cancer treatment plans of 19 patients using two treatment planning systems, Pinnacle 9.10 and RayStation 11, with similar dose calculation algorithms. …”
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Integrative bioinformatics and machine learning identify key crosstalk genes and immune interactions in head and neck cancer and Hodgkin lymphoma by Meiling Qin, Xinxin Li, Xun Gong, Yuan Hu, Min Tang

“…The intersection of HNSCC DEGs and HL-related modules was evaluated using protein–protein interaction (PPI) network analysis. …”
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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

“…S100A8/A9 can also be used as a biomarker for validity differentiation of SMPP when medical conditions are limited.…”
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Development and Validation of a Clinical Risk Model for Predicting Malignancy in Patients with Thyroid Nodules by Shiva Borzouei, Ali Safdari, Erfan Ayubi

“…Generally, there was no difference among the six ML algorithms in terms of prognostic performance; however, the prognostic parameters of GLM and LDA algorithms were higher than the others. …”
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Lipid-Metabolism-Related Gene Signature Predicts Prognosis and Immune Microenvironment Alterations in Endometrial Cancer by Zhangxin Wu, Yufei Nie, Deshui Kong, Lixiang Xue, Tianhui He, Kuaile Zhang, Jie Zhang, Chunliang Shang, Hongyan Guo

“…Tumor immune infiltration patterns were evaluated using single-sample Gene Set Enrichment Analysis (ssGSEA), Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data (ESTIMATE), and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms. …”
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A novel ensemble of hybrid starling murmuration optimized stacked gated Ghostnets for robust classification of DDoS attacks by P. Mamatha, S. Balaji, S. Sai Anuraghav

“…Due to hostile user techniques and the complexity of DDoS, advanced defensive measures are mandatorily required. As the algorithms of Artificial Intelligence (AI) serves as a key factor in developing the the intelligent intrusion detection systems which accurately differentiates the known and unknown attacks. …”
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Optimizing skin cancer screening with convolutional neural networks in smart healthcare systems. by Ali Raza, Akhtar Ali, Sami Ullah, Yasir Nadeem Anjum, Basit Rehman

“…A research used an optimized CNN and ResNet152V2 with the HAM10000 dataset to differentiate between the seven forms of skin cancer. …”
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Transcriptome Derived Artificial neural networks predict PRRC2A as a potent biomarker for epilepsy by Wayez Naqvi, Prekshi Garg, Prachi Srivastava

“…The model’s performance was evaluated using the “pROC” R package, and an AUC of 0.720 was obtained, indicating that the model had excellent classification accuracy. …”
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Clinical application and immune infiltration landscape of stemness‐related genes in heart failure by Wenting Yan, Yanling Li, Gang Wang, Yuan Huang, Ping Xie

“…Stemness refers to the self‐renewal and differentiation ability of cells. However, little is known about the heart's stemness properties. …”
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Construction of a novel CD8T cell-related index for predicting clinical outcomes and immune landscape in ovarian cancer by combined single-cell and RNA-sequencing analysis by Yu Zhang, Peng Wan, Liangliang Wang, Ruiping Ren

“…Furthermore, immune landscape analysis was performed using CIBERSORT, ssGSEA, TIMER, and ESTIMATE algorithms. Tumor mutation burden (TMB) analysis and drug sensitivity analysis were used to evaluate the potential predictive value of CCAI. …”
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