Near-Infrared Spectroscopy Machine-Learning Spectral Analysis Tool for Blueberries (<i>Vaccinium corymbosum</i>) Cultivar Discrimination by Pedro Ribeiro, Maria Inês Barbosa, Clara Sousa, Pedro Miguel Rodrigues

“…Spectra were acquired from fresh blueberry leaves collected from two geographic regions and across three seasons. Machine-learning-based models, selected from a pool of 10 classifiers based on their discrimination power under a twofold stratified cross-validation process, were trained/tested with 1 to 20 components obtained by the application of data dimensionality reduction (DDR) techniques (dictionary learning, factor analysis, fast individual component analysis, and principal component analysis) to different near-infrared (NIR) spectra regions’ data, to either analyze a single spectral region and season or combine spectral regions and/or seasons for each side of the blueberry leaf. …”
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Comparative analysis of inflow forecasting using machine learning and statistical techniques: case study of Mangla reservoir and Marala Headworks by Muhammad Muneeb Khan, Muhammad Kaleem Sarwar, Muhammad Awais Zafar, Muhammad Rashid, Muhammad Atiq Ur Rehman Tariq, Saif Haider, Abdelaziz M. Okasha, Ahmed Z. Dewidar, Mohamed A. Mattar, Ali Salem, Ali Salem

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Integrating transcriptomic data with a novel drug efficacy prediction model for TCM active compound discovery by Yingcan Li, Yu Shen, Yezi Cai, Yulin zhang, Jiahui Gao, Lei Huang, Weinuo Si, Kai Zhou, Shan Gao, Qichao Luo

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Advancing Seabed Bedform Mapping in the Kuźnica Deep: Leveraging Multibeam Echosounders and Machine Learning for Enhanced Underwater Landscape Analysis by Łukasz Janowski

“…Advances in remote sensing, particularly, object-based image analysis (OBIA) and machine learning, have significantly improved geospatial data analysis for underwater landscapes. …”
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Machine Learning-Assisted 3D Flexible Organic Transistor for High-Accuracy Metabolites Analysis and Other Clinical Applications by Caizhi Liao, Huaxing Wu, Luigi G. Occhipinti

“…Machine learning algorithms further enhance the analytical capabilities of FOT sensors by effectively processing complex data, identifying patterns, and predicting diagnostic outcomes with 100% high accuracy. …”
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Integrating Machine Learning and Pathway Analysis for Precision Medicine in Type 2 Diabetes: Predictive Modeling and Therapeutic Target Identification by Iram Wajahat, Fazel Keshtkar, Syed Ahmad Chan Bukhari

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Construction of a transfer learning-based depression detection model for female breast cancer patients: text sentiment analysis by Jiaqi Fu, Shisi Deng, Wanting Zheng, Chunrao Zheng, Jianhong Liu, Wenji Li, Yinghua Zeng, Hongpo Xie, Yuchang Mai, Chaixiu Li, Jie Lai, Yujie Zhang, Zihan Guo, Jianyao Tang, Chuhan Zhong, Huihui Zhao, Yanni Wu

“…However, the unstructured and vast nature of these textual expressions poses challenges for manual analysis. To address this, our research team employed transfer learning methods to efficiently process and analyze large-scale text data for depression detection. …”
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Validation and contextualization of professional learning communities scale in secondary schools: A factorial analysis from Awi Zone, Ethiopia by Mulat Alemu, Alemayehu Bishaw, Tadesse Melesse

“…Data were collected from 397 randomly selected secondary school teachers. …”
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Predicting Epileptic Seizures Using EfficientNet-B0 and SVMs: A Deep Learning Methodology for EEG Analysis by Yousif A. Saadoon, Mohamad Khalil, Dalia Battikh

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Supervised machine learning algorithms for the classification of obesity levels using anthropometric indices derived from bioelectrical impedance analysis by Rodrigo Yáñez-Sepúlveda, Aldo Vásquez-Bonilla, Rodrigo Olivares, Pablo Olivares, Juan Pablo Zavala-Crichton, Claudio Hinojosa-Torres, Catalina Muñoz-Strale, Frano Giakoni-Ramírez, Josivaldo de Souza-Lima, Jacqueline Páez-Herrera, Jorge Olivares-Arancibia, Tomás Reyes-Amigo, Guillermo Cortés-Roco, Juan Hurtado-Almonacid, Eduardo Guzmán-Muñoz, Nicole Aguilera-Martínez, José Francisco López-Gil, Boryi A. Becerra-Patiño, Juan David Paucar-Uribe, Exal Garcia-Carrillo, Vicente Javier Clemente-Suárez

“…This study aimed to evaluate and compare the performance of various supervised machine learning algorithms in classifying obesity levels using anthropometric indices derived from bioelectrical impedance analysis (BIA). …”
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Analysis of Deep Learning-Based Frameworks for Fault Detection in Big Research Infrastructures: A Case Study of the SOLARIS Synchrotron by Michal Piekarski, Joanna Jaworek-Korjakowska, Adriana Izabela Wawrzyniak

“…This paper presents an in-depth analysis of multi-modal, deep learning-based frameworks for fault detection within big research infrastructures, with a specific focus on synchrotron facilities. …”
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Utilization of digital technology-based learning on computational thinking ability of elementary school students: A Meta-analysis study by Ary Kiswanto Kenedi, Sujarwo, Fery Muhamad Firdaus, Yoppy Wahyu Purnomo

“…Data analysis was aided by the OPENMEE application. …”
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An exploratory mixed-methods sentiment analysis of a social-emotional learning (SEL)-informed grant writing workshop in the biosciences by Miroslav Suzara, Courtney Peña, Crystal Botham

“…To address this, we conducted a grant writing workshop that explicitly incorporated social-emotional learning (SEL) into its delivery. Through a comparative sentiment analysis, we used pre-post survey data (n = 31) to understand what effect the workshop had on participants’ perceptions and attitudes toward grant writing. …”
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AI-Driven Integration of Deep Learning With Lung Imaging, Functional Analysis, and Blood Gas Metrics for Perioperative Hypoxemia Prediction by Kecheng Huang, Chujun Wu, Rongpeng Pi, Jieyu Fang

“… This viewpoint article explores the transformative role of artificial intelligence (AI) in predicting perioperative hypoxemia through the integration of deep learning with multimodal clinical data, including lung imaging, pulmonary function tests, and arterial blood gas (ABG) analysis. …”
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Analysis of Weak Links in the Mechanized Mining of Underground Metal Mines: Insights from Machine Learning and SHAP Explainability Models by Chengye Yang, Keping Zhou, Jielin Li

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GRL-ITransformer: An Intelligent Method for Multi-Wind-Turbine Wake Analysis Based on Graph Representation Learning With Improved Transformer by Kang Han, Li Xu

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Machine learning for automated electrical penetration graph analysis of aphid feeding behavior: Accelerating research on insect-plant interactions. by Quang Dung Dinh, Daniel Kunk, Truong Son Hy, Vamsi Nalam, Phuong D Dao

“…However, the traditional manual analysis of EPG waveform data is time-consuming and labor-intensive, limiting research throughput. …”
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Cross border railway trade and urban development in minority ethnic autonomous regions: causal analysis with double machine learning by Chang Gao, Lianjun Yao, Xueyuan Wang

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Cellular interactions and Ion channel signatures in atrial fibrillation remodeling: insights from single-cell analysis and machine learning by Bin He, Yan Cheng, Juan Wang, Ya Zhan, YanQun Liu

“…In the electrical remodeling investigation, ion channel gene sets and gene expression data were utilized alongside LASSO and SVM machine-learning algorithms combined with ROC curve analysis. …”
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Analysis of the Effect of Branched Chain Amino Acids on Muscle Health Information of Swimmers Based on Multisensor Fusion and Deep Learning by Shimeng Huang, Qiulan Luo, Jingwen Liao

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