Exploring the capabilities of hyperspectral remote sensing for soil texture evaluation by Mohammad Hosseinpour-Zarnaq, Mahmoud Omid, Fereydoon Sarmadian, Hassan Ghasemi-Mobtaker, Reza Alimardani, Pouya Bohlol

“…Additionally, we compared the performance of random forest (RF) algorithms with partial least squares regression (PLSR), multiple linear regression (MLR), support vector machine regression (SVR), decision trees (DTs), and multilayer perceptron (MLP) neural networks, addressing the effects of feature selection and irregular soil data on the modeling procedure. …”
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Electric Motor Vibration Signal Classification Using Wigner–Ville Distribution for Fault Diagnosis by Jian-Da Wu, Wen-Jun Luo, Kai-Chao Yao

“…The brushless motor vibration signal is imaged using the WVD analysis method to extract the vibration signal characteristics. …”
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A prospective, phase II, neoadjuvant study based on chemotherapy sensitivity in HR+/HER2‐ breast cancer‐FINEST study by Li Chen, Wen‐Ya Wu, Fei Liang, Guang‐Yu Liu, Ke‐Da Yu, Jiong Wu, Gen‐Hong Di, Lei Fan, Zhong‐Hua Wang, Jun‐Jie Li, Zhi‐Ming Shao

“…Peripheral blood and core‐needle biopsy (CNB) samples were collected before treatment, followed by a next‐generation sequencing (NGS) panel detection and similarity network fusion (SNF) typing through digital pathology data. …”
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CLUMM: Contrastive Learning for Unobtrusive Motion Monitoring by Pius Gyamenah, Hari Iyer, Heejin Jeong, Shenghan Guo

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Construction of the preoperative staging prediction model for cervical cancer based on deep learning and MRI: a retrospective study by Xuhao Dai, Xiaoxian Ye, Jiangping Ren, Jiming Yang, Yingying Zhou, Zhaoyang Ma, Pengrong Lou

“…Traditional staging methods rely on manual imaging analysis, which is subjective and time-consuming. …”
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Tuning the Legacy Survey of Space and Time Observing Strategy for Solar System Science: Incremental Templates in Year 1 by James E. Robinson, Megan E. Schwamb, R. Lynne Jones, Mario Jurić, Peter Yoachim, Bryce T. Bolin, Colin O. Chandler, Steven R. Chesley, Grigori Fedorets, Wesley C. Fraser, Sarah Greenstreet, Henry H. Hsieh, Lauren J. McGinley, Stephanie R. Merritt, Cyrielle Opitom, John K. Parejko

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Acute Stroke Severity Assessment: The Impact of Lesion Size and Functional Connectivity by Karolin Weigel, Christian Gaser, Stefan Brodoehl, Franziska Wagner, Elisabeth Jochmann, Daniel Güllmar, Thomas E. Mayer, Carsten M. Klingner

“…Conclusions: The findings highlight lesion size as a reliable early marker of stroke severity and underscore the complementary value of functional connectivity analysis. Integrating rs-fMRI into clinical stroke imaging protocols offers a potential approach for refining prognostic models. …”
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Inertial sensor-based heel strike and energy expenditure prediction using a hybrid machine learning approach by Kethohalli R Vidyarani, Viswanath Talasila, Raafay Umar, Venkatesan Prem, Ravi Prasad K Jagannath, Gurusiddappa R Prashanth

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Classification of Dyslexia Among School Students Using Deep Learning by Alia Hussein, Ahmed Talib Abdulameer, Ali Abdulkarim, Husniza Husni, Dalia Al-Ubaidi

“…This study proposes a novel approach for diagnosing dyslexic children using spectrogram analysis and convolutional neural networks (CNNs). …”
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Exploring Artificial Intelligence for Enhanced Endodontic Practice: Applications, Challenges, and Future Directions by Santosh R. Patil, Mohmed Isaqali Karobari

“…The review methodology involves a critical analysis of existing literature, highlighting advancements in diagnostic imaging, predictive analytics, and procedural assistance. …”
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Sensing technology for greenhouse tomato production: A systematic review by Jingxin Yu, Jiang Liu, Congcong Sun, Jiaqi Wang, Jianchao Ci, Jing Jin, Ni Ren, Wengang Zheng, Xiaoming Wei

“…The review covers four key areas: (1) a comprehensive analysis of critical environmental factors influencing tomato growth, such as temperature, humidity, light intensity, and CO2 concentration; (2) an exploration of high-throughput, non-destructive sensing technologies, including chlorophyll fluorescence imaging, infrared CO2 sensing, and multispectral imaging; (3) an investigation of the algorithms based on multi-sensor data fusion and data-driven diagnostic systems for disease detection and growth forecasting; and (4) a discussion on potential research topics in the future to address the limitations of the existing methods. …”
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Computer-Aided Diagnosis Techniques for Brain Tumor Segmentation and Classification Using MRI by Gadicha A. B., Kale Prachi V., Dalvi G. D., Mohod M. M., Pakhale S. C., Khan S. M.

“…This paper presents a comprehensive review of various AI-driven techniques, including traditional ML models, deep convolutional neural networks, and hybrid systems, that have been employed for the automatic detection, segmentation, and categorization of brain tumors using MRI data. …”
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Current Topics on the Integration of Artificial Intelligence in the Histopathological and Molecular Diagnosis of Uveal Melanoma by Serena Salzano, Giuseppe Broggi, Andrea Russo, Teresio Avitabile, Antonio Longo, Rosario Caltabiano, Manuel Mazzucchelli

“…<b>Methods:</b> This work delves into the application of AI technologies such as machine learning (ML), deep learning (DL), and convolutional neural networks (CNNs) in various diagnostic procedures, molecular profiling, and predictive analysis. …”
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Clinical and cost-effectiveness of detailed anomaly ultrasound screening in the first trimester: a mixed-methods study by Jehan N Karim, Helen Campbell, Pranav Pandya, Edward C F Wilson, Zarko Alfirevic, Trish Chudleigh, Elizabeth Duff, Jane Fisher, Hilary Goodman, Lisa Hinton, Christos Ioannou, Edmund Juszczak, Louise Linsell, Heather L Longworth, Kypros H Nicolaides, Anne Rhodes, Gordon Smith, Basky Thilaganathan, Jim Thornton, Gillian Yaz, Oliver Rivero-Arias, Aris T Papageorghiou

“…Design Systematic review and meta-analysis. Nationwide survey. Analysis of National Congenital Anomaly Disease Registry data. …”
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Genomic structural equation modeling reveals latent phenotypes in the human cortex with distinct genetic architecture by Rajendra A. Morey, Yuanchao Zheng, Henry Bayly, Delin Sun, Melanie E. Garrett, Marianna Gasperi, Adam X. Maihofer, C. Lexi Baird, Katrina L. Grasby, Ashley A. Huggins, Courtney C. Haswell, Paul M. Thompson, Sarah Medland, Daniel E. Gustavson, Matthew S. Panizzon, William S. Kremen, Caroline M. Nievergelt, Allison E. Ashley-Koch, Mark W. Logue

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Using artificial intelligence methods for shear travel time prediction: A case study of Facha member, Sirte basin, Libya by Bahia Ben Ghawar, Moncef Zairi, Samir Bouaziz

“…Based on principle component analysis, two wireline data sets were chosen to build intelligent models for prediction of shear travel time. …”
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Deep Learning Methods and UAV Technologies for Crop Disease Detection by S. G. Mudarisov, I. R. Miftakhov

“…The paper also addresses challenges associated with the use of unmanned aerial vehicles, such as data quality limitations, the complexity of processing large volumes of images, and the need for the development of more advanced models. …”
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Research Progress on Micro/Nanopore Flow Behavior by Jinbo Yu, Meng Du, Yapu Zhang, Xinliang Chen, Zhengming Yang

“…Moreover, the integration of artificial intelligence (e.g., data-driven modeling and physics-informed neural networks) is accelerating data interpretation and multiscale modeling, offering improved predictive capabilities. …”
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DIGITAL MOBILITY OF THE FUTURE SPECIALIST: CURRENT TRENDS by Leonov Maksym

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Digital marketing and customer orientation as predictors of sustainability in tourism SMES by Nancy Tupac Yupanqui Lima, Karla Liliana Haro-Zea, Robin Alexander Díaz Saavedra

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