Modeling quinoa growth under saline and water-limiting conditions using SWAP-WOFOST by Diana C. Estrella Delgado, Tom De Swaef, Jan Vanderborght, Eric Laloy, Gerda Cnops, Maarten De Boever, Abdelaziz Hirich, Ayoub El Mouttaqi, Sarah Garré

“…Calibration and parameter uncertainty was performed using the DiffeRential Evolution Adaptive Metropolis (DREAMzs) algorithm on key parameters identified via sensitivity analysis using the Morris method. …”
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Identification of serum tRNA-derived small RNAs biosignature for diagnosis of tuberculosis by Zikun Huang, Qing Luo, Cuifen Xiong, Haiyan Zhu, Chao Yu, Jianqing Xu, Yiping Peng, Junming Li, Aiping Le

“…By utilizing cross-validation with a random forest algorithm approach, the training cohort achieved a sensitivity of 100% and specificity of 100%. …”
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Integration of YOLOv9 Segmentation and Monocular Depth Estimation in Thermal Imaging for Prediction of Estrus in Sows Based on Pixel Intensity Analysis by Iyad Almadani, Aaron L. Robinson, Mohammed Abuhussein

“…This comparison allows us to evaluate the improvements in accuracy and performance achieved with the updated model. …”
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ANALISIS OF THE INFLUENCE OF THE MAIN PARAMETERS AND CONDITION OF WORK OF AIRCRAFT CESN ON THE EFFICENCY OF THEIR USE METHODS OF MATHEMATICAL MODELING by V. I. Troitsky

“…The aim of the numerical experiments was the analysis of the influence of the main parameters (characteristics of the radiometer and antenna, a means of reviewing the space, parameters of the current image and the reference image, methods for image processing (algorithms for image correlation), conditions of the equipment operation (the speed and altitude of aircraft, the evolution of media) on the efficiency of CESN. …”
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Mutational landscape and DNA methylation-based classification of squamous cell carcinoma and urothelial carcinoma by Min Ren, Midie Xu, Chen Chen, Ran Wei, Qianlan Yao, Liqing Jia, Peng Qi, Qifeng Wang, Qianming Bai, Xiaoli Zhu, Sheng Wu, Qinghua Xu, Xiaoyan Zhou

“…On the basis of public datasets and analyses via various machine learning algorithms, a DNA methylation-based classification containing 106 features by the CatBoost algorithm was constructed and reached an accuracy of 98.79% (490/496) in the training set from PanCanAtlas datasets. …”
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Efficient Pruning of Detection Transformer in Remote Sensing Using Ant Colony Evolutionary Pruning by Hailin Su, Haijiang Sun, Yongxian Zhao

“…To retain the original network’s performance as much as possible, we combine population evolution and ant colony algorithms for dynamic search processes to automatically find efficient sparse sub-networks. …”
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Identification of a PANoptosis-related long noncoding rna risk signature for prognosis and immunology in colon adenocarcinoma by Yuekai Cui, Jie Mei, Shengsheng Zhao, Bingzi Zhu, Jianhua Lu, Hongzheng Li, Binglong Bai, Weijian Sun, Wenyu Jin, Xueqiong Zhu, Shangrui Rao, Yongdong Yi

“…Using the CIBERSORT algorithm and gene set enrichment analysis, variations in infiltrating immune cells and immune processes were observed between the two risk groups. …”
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Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn’s disease by Zhuoyan Chen, Weimin Cai, Yuanhang He, Tianhao Mei, Yuxuan Zhang, Shiyu Li, Yiwen Hong, Yuhao Chen, Huiya Ying, Yuan Zeng, Fujun Yu

“…Z score standardization and independent sample t test were applied to identify optimal predictive features, which were then utilized in seven ML algorithms for training and validation. Model performance was assessed through receiver-operating characteristic curves, precision–recall curves, and calibration curve analyses, evaluating accuracy and clinical applicability. …”
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Single-Cell Analysis Reveals Aspirin Restores Intervertebral Disc Integrity via Ferroptosis Regulation by Niu H, Qi H, Zhang P, Meng H, Liu N, Zhang D

“…Subtype identification, differential expression analysis, enrichment analysis, and cell proportion analysis were conducted to explore functional alterations in various nucleus pulposus cell (NPC) subpopulations. …”
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A Novel Rubber Composite Sleeper-Deformation-Prediction Model Based on Response Surface Method (RSM) and Machine Learning (ML) Techniques by Abdulmumin Ahmed Shuaibu, Zhiping Zeng, Ibrahim Hayatu Hassan, Wang Weidong, Hassan Suleiman Otuoze, Suleiman Abdulhakeem, Bushrah Baba Abdulrahman

“…Simultaneously, lateral deformation was recorded using linear variable differential transducer (LVDT) displacement sensors. …”
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Identification of progression-related genes and construction of prognostic model for chronic kidney disease by machine learning by Bingkun Zhou, Hu Zhou, Xiaodong Huang, Shijie Liu

“…However, there is currently a lack of CKD prognostic prediction models based on transcriptomics and machine learning.MethodsUtilizing weighted correlation network analysis (WGCNA) and random forest algorithms in GSE137570, three core gene sets of different sizes were constructed, which were externally validated in GSE66494 and GSE180394, and evaluated for their predictive performance in GSE45980 by receiver operating characteristic (ROC) curves. …”
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Finding White Dwarfs’ Hidden Companions Using an Unsupervised Machine Learning Technique by Xabier Pérez-Couto, Minia Manteiga, Eva Villaver

“…White dwarfs (WD) with main-sequence (MS) companions are crucial probes of stellar evolution. However, due to the significant difference in their luminosities, the WD is often outshined by the MS star. …”
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Detection and Analysis of Malicious Software Using Machine Learning Models by Selman Hızal, Ahmet Öztürk

“…The continuous evolution of malware poses a significant challenge in cybersecurity, adapting to technological advancements despite implemented security measures. …”
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Spatial and temporal heterogeneity in high-grade serous ovarian cancer: a phylogenetic analysis. by Roland F Schwarz, Charlotte K Y Ng, Susanna L Cooke, Scott Newman, Jillian Temple, Anna M Piskorz, Davina Gale, Karen Sayal, Muhammed Murtaza, Peter J Baldwin, Nitzan Rosenfeld, Helena M Earl, Evis Sala, Mercedes Jimenez-Linan, Christine A Parkinson, Florian Markowetz, James D Brenton

“…The objective of this study was to determine whether intra-tumour genetic heterogeneity resulting from clonal evolution and the emergence of subclonal tumour populations in HGSOC was associated with the development of resistant disease.…”
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Application of the LDA model to identify topics in telemedicine conversations on the X social network by Mario Sierra Martín, Fang-Wei Chen, Pilar Alarcón Urbistondo

“…Abstract The evolution experienced by global society, in the post-COVID 19 era, is marked by the quite obligatory use of digital media in many sectors, as is the case for the health sector. …”
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Molecular sub-classification of renal epithelial tumors using meta-analysis of gene expression microarrays. by Thomas Sanford, Paul H Chung, Ariel Reinish, Vladimir Valera, Ramaprasad Srinivasan, W Marston Linehan, Gennady Bratslavsky

“…<h4>Purpose</h4>To evaluate the accuracy of the sub-classification of renal cortical neoplasms using molecular signatures.…”
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Identification and analysis of the endoplasmic reticulum stress hub genes in sepsis-associated ARDS by Ling Gao, Tingting Liu, Xiaoyan Li

“…The aim of this study was to identify and analyze hub genes related to ERS in sepsis-associated ARDS using bioinformatics and machine learning algorithms, which may serve as diagnostic markers and therapeutic targets. …”
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From Biopsy to Diagnosis: Navigating Aggressive B-Cell Lymphomas in Practice by Georgian Halcu, Anca Evsei-Seceleanu, Mihai Cerbu, Marina Alina Bara, Andrei Turbatu, Mihail Constantin Ceausu

“…This review presents a practical method for differentiating DLBCL from other aggressive B-cell neoplasms, such as Burkitt lymphoma, B-lymphoblastic lymphoma, and mantle cell lymphoma. …”
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Early detection of bacterial pneumonia by characteristic induced odor signatures by Kim Arnold, Alejandro Gómez-Mejia, Miguel de Figueiredo, Julien Boccard, Kapil Dev Singh, Serge Rudaz, Pablo Sinues, Annelies S. Zinkernagel

“…The detected VOCs were analyzed using a pre- and post-processing algorithm along with ANOVA and RASCA statistical evaluation methods. …”
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Lactylation Modification as a Promoter of Bladder Cancer: Insights from Multi-Omics Analysis by Yipeng He, Lingyan Xiang, Jingping Yuan, Honglin Yan

“…Functional enrichment analysis, tumor microenvironment analysis, and treatment response evaluation were performed on the high- and low-risk groups. …”
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