Machine learning-based prediction of scale formation in produced water as a tool for environmental monitoring by Arash Tayyebi, Ali Alshami, Erfan Tayyebi, Ademola Owoade, MusabbirJahan Talukder, Nadhem Ismail, Zeinab Rabiei, Xue Yu, Glavic Tikeri

“…This method not only improves understanding of water chemistry but also enhances environmental analyses and monitoring by predicting scale formation as a potential form of contamination, which can help assess and maintain water quality in industrial settings. …”
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Development of a deep learning system for predicting biochemical recurrence in prostate cancer by Lu Cao, Ruimin He, Ao Zhang, Lingmei Li, Wenfeng Cao, Ning Liu, Peisen Zhang

“…Increasing the number of WSIs for each patient improves the performance of the prediction system. …”
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Exploring the Current Applications and Future Implications of Artificial Intelligence in Public Health Dentistry: A Narrative Review by Tanushri Mahendra Dalvi, Rajeshri Kotwadekar, Shrivardhan R Kalghatgi, Priyanka Paul Madhu, Priyanka Methildeotare

“…AI technologies such as machine learning, deep learning, and natural language processing have been able to show an enormously huge scale capacity for improvement in oral health outcomes at the population level, particularly among disadvantaged groups. …”
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Analysis of types of medical interventions for patients with pancreatic adenocarcinoma in hospitals of Saint Petersburg for the period from 2014 to 2020 by V. E. Moiseenko, A. V. Pavlovsky, D. A. Granov, L. V. Kochorova, N. I. Vishnjakov, V. V. Hizha, A. V. Yazenok, N. Ju. Shirshova, L. A. Solovyova

“…The data obtained should be taken into account when improving and developing new programs for the detection of pancreatic adenocarcinoma at early stages. …”
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Developing an Uncrewed Aerial Vehicle (UAV)-Based Prediction Model for the Rice Harvest Index Using Machine Learning by Zhaoyang Pan, Zhanhua Lu, Liting Zhang, Wei Liu, Xiaofei Wang, Shiguang Wang, Hao Chen, Haoxiang Wu, Weicheng Xu, Youqiang Fu, Xiuying He

“…Based on the above characteristics, this study used a variety of machine learning algorithms to construct a harvest index prediction model. …”
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Ethical Foundations of AI-Driven Avatars in the Metaverse for Innovation and User Privacy by Ammar Almomani, Ahmad Al-Qerem, Mohammad Alauthman, Amjad Aldweesh, Samer Aoudi, Said A. Salloum

“…Validation through case study analysis demonstrates significant improvements in privacy protection metrics, substantial reduction in identity theft vulnerabilities, and marked enhancement in user autonomy controls compared to existing frameworks. …”
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Earth Observation Data to Support Environmental Justice: Linking Non‐Permitted Poultry Operations to Social Vulnerability Indices by Mirela G. Tulbure, Júlio Caineta, Brooke Cox, Stephen V. Stehman, Ayse Ercumen, Rebecca Witter, Ryan Emanuel, Dana E. Powell, Kemp Burdette, Sherri White‐Williamson, Shea Tuberty

“…We removed 51.8% of misclassified features in NC and 61.5% across the US, significantly improving data set accuracy. Spatial analysis, including Local Indicators of Spatial Association, revealed that poultry CAFOs often cluster in census tracts with high Social Vulnerability Index (SVI) scores, indicating potential EJ issues. …”
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GAT-ADNet: Leveraging Graph Attention Network for Optimal Power Flow in Active Distribution Network With High Renewables by Dinesh Kumar Mahto, Mahipal Bukya, Rajesh Kumar, Akhilesh Mathur, Vikash Kumar Saini

“…Implementing traditional OPF algorithms can be challenging for large-scale networks with complex topologies and constraints. …”
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A nomogram for predicting the nature of thyroid adenomatoid nodules on ultrasound: a dual-center study by Sheng Cheng, Xian-Tao Zeng, Xia Liang, Zhi-Liang Hong, Jian-Chuan Yang, Zi-Ling You, Song-Song Wu

“…By incorporating clinical and radiomics features, the R-C Nomogram can reduce unnecessary biopsies and guide treatment decisions such as ultrasound-guided thermal ablation, improving patient management and reducing healthcare resource burden.…”
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Machine Learning-Based Detection of Archeological Sites Using Satellite and Meteorological Data: A Case Study of Funnel Beaker Culture Tombs in Poland by Krystian Kozioł, Natalia Borowiec, Urszula Marmol, Mateusz Rzeszutek, Celso Augusto Guimarães Santos, Jerzy Czerniec

“…The proposed approach not only improves site detection but also reduces operational costs by concentrating resources on optimal survey conditions. …”
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Investigating factors influencing quality of life in thyroid eye disease: insight from machine learning approaches by Haiyang Zhang, Shuo Wu, Lehan Yang, Chengjing Fan, Huifang Chen, Hui Wang, Tianyi Zhu, Yinwei Li, Jing Sun, Xuefei Song, Huifang Zhou, Terry J Smith, Xianqun Fan

“…Identifying effective interventions and considering specific demographic characteristics are essential to improving the QOL of patients with TED.…”
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Electrophysiological changes in the acute phase after deep brain stimulation surgery by Lucia K. Feldmann, Diogo Coutinho Soriano, Jeroen Habets, Valentina D'Onofrio, Jonathan Kaplan, Varvara Mathiopoulou, Katharina Faust, Gerd-Helge Schneider, Doreen Gruber, Georg Ebersbach, Hayriye Cagnan, Andrea A. Kühn

“…The microlesion effect is a well-known phenomenon of transient clinical improvement in the acute post-operative phase. While beta band activity is confirmed as a reliable biomarker for bradykinesia using chronic recordings, little is known about the ideal time point for initial electrophysiology-based programming. …”
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On-Demand Gait-Synchronous Electrical Cueing in Parkinson's Disease Using Machine Learning and Edge Computing: A Pilot Study by Ardit Dvorani, Constantin Wiesener, Christina Salchow-Hommen, Magdalena Jochner, Lotta Spieker, Matej Skrobot, Hanno Voigt, Andrea Kuhn, Nikolaus Wenger, Thomas Schauer

“…By avoiding this we aim at improving usability, robustness, and detection delay. …”
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AirQuaNet: A Convolutional Neural Network Model With Multi-Scale Feature Learning and Attention Mechanisms for Air Quality-Based Health Impact Prediction by Sreeni Chadalavada, Suleyman Yaman, Abdulkadir Sengur, Ravinesh C. Deo, Abdul Hafeez-Baig, Tracy Kolbe-Alexander, Niranjana Sampathila, U. Rajendra Acharya

“…Residual connections are employed to prevent vanishing gradient issues during training, and the self-attention mechanism dynamically weights informative inputs, improving the model’s attention towards informative pollutant features. …”
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Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT by Hao-Nan Zhu, Yi-Fan Guo, YingMin Lin, Zhi-Chao Sun, Xi Zhu, YuanZhe Li

“…Background: Bone metastasis from breast cancer significantly elevates patient morbidity and mortality, making early detection crucial for improving outcomes. This study utilizes radiomics to analyze changes in the thoracic vertebral bone marrow microenvironment from chest computerized tomography (CT) images prior to bone metastasis in breast cancer, and constructs a model to predict metastasis. …”
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TomaFDNet: A multiscale focused diffusion-based model for tomato disease detection by Rijun Wang, Rijun Wang, Yesheng Chen, Fulong Liang, Xiangwei Mou, Xiangwei Mou, Guanghao Zhang, Hao Jin

“…Compared to the baseline YOLOv8 model, TomaFDNet achieves a 4.2% improvement in mAP, which is statistically significant (P < 0.01). …”
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The different member equivalent circulating density prediction model and drilling parameter optimization under narrow density window by Wanchun Zhao, Wanchun Zhao, Zhipeng Yang, Tingting Wang, Yan Zhou, Wei Song, Jingrun Li, Peihong Zhai

“…The model uses nonlinear regression algorithms to predict ECD values for different members. …”
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An innovative UAV-based approach for estimating crop stand counts amidst weed infestation by Gurjinder S. Baath, Arun Bawa, Bala Ram Sapkota, K. Colton Flynn, Sayantan Sarkar, Douglas R. Smith

“…However, most existing algorithms assume clean crop rows and do not account for common weed infestation. …”
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Construction and validation of immune prognosis model for lung adenocarcinoma based on machine learning by Jinyu Zheng, Xiaoyi Xu, Xianguo Chen, Xianshuai Li, Miao Fu, Yiping Zheng, Jie Yang

“…Identifying novel prognostic biomarkers is essential for improving patient outcomes.MethodsTranscriptomic and clinicopathological data from TCGA (55 tumor samples and 38 normal samples) were used to construct a prognostic model, with 30 samples for internal validation. …”
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Recent advances in anion exchange membrane technology for water electrolysis: a review of progress and challenges by Abdul Qayoom, Muhammad Shakeel Ahmad, H. Fayaz, Atika Qazi, Jeyraj Selvaraj, Rahadian Zainul, Krismadinata, Nasrudin Abd Rahim, Farruh Atamurotov, Thien Khanh Tran, Basma Souayeh, Natei Ermias Benti

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