Geospatial analysis of landslide susceptibility and safe relocation zones: Insights from recent disasters in Gofa Zone, Southern Ethiopia by Natnael Agegnehu Ayele, Esubalew Mulugeta Engda, Taye Teshome Terefe, Eyasu Leta, Talema Moged Reda, Muralitharan Jothimani

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Geo-Intelligence for Resilient Land-use Planning by John Kiema

“… Geo-Intelligence integrates geospatial technologies such as satellite imagery, remote sensing, Geographic Information Systems (GIS), and Artificial Intelligence (AI) to gather, process, and analyze spatial data for decision-making. This study explores the application of Geo-Intelligence in resilient land use planning in Kenya’s Lower Eastern Region, aiming to optimize land potential amidst climate change challenges. …”
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Probabilistic optimal power flow in wind energy integrated power system based on the K‐medoids data clustering method considering correlated uncertain variables by Saeed Badoozadeh, Nazila Nikdel, Sadjad Galvani, Mohammad Farhadi‐Kangarlu

“…Probabilistic assessment of power systems is essential to evaluate uncertainties’ effects and make reasonable decisions. …”
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Real-time morphological and dosimetric adaptation in nasopharyngeal carcinoma radiotherapy: insights from autosegmented fractional fan-beam CT by Xiao-li Yu, Jiang Hu, Yu-xian Yang, Guang-yu Wang, Xin Yang, Wen-chao Diao, Lu Liu, Xiao-bo Jiang, Chen-di Xu, Liu-wen Lin, Le-cheng Jia, Hua Li, Yan-fei Liu, Ying Sun, Guan-qun Zhou

“…Abstract Background To quantify morphological and dosimetric variations in nasopharyngeal carcinoma (NPC) radiotherapy via autosegmented fan-beam computed tomography (FBCT) and to inform decision-making regarding appropriate objectives and optimal timing for adaptive radiotherapy (ART). …”
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The holistic enterprise management approach: including labor migration into modeling the dynamics of the influence factors on functioning by Yaroslav Kotlyarevskyy, Vsevolod Senkivskyy, Iryna Pikh, Taras Shyra, Alona Kudriashova, Ihor Berest, Andriy Shtangret

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Blockchain enabled deep learning model with modified coati optimization for sustainable healthcare disease detection and classification by Heba G. Mohamed, Fadwa Alrowais, Fahd N. Al-Wesabi, Mesfer Al Duhayyim, Anwer Mustafa Hilal, Abdelwahed Motwakel

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YED-Net: Yoga Exercise Dynamics Monitoring with YOLOv11-ECA-Enhanced Detection and DeepSORT Tracking by Youyu Zhou, Shu Dong, Hao Sheng, Wei Ke

“…Future work aims to integrate 3D pose estimation to develop a closed-loop biomechanical analysis system, thereby advancing sports science toward intelligent decision-making paradigms.…”
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Development and validation of a radiomics-based nomogram for predicting pathological grade of upper urinary tract urothelial carcinoma by Yanghuang Zheng, Hongjin Shi, Shi Fu, Haifeng Wang, Xin Li, Zhi Li, Bing Hai, Jinsong Zhang

“…The area under the receiver operating characteristic curve (AUC values), accuracy, sensitivity, and specificity were assessed for model performance evaluation. Decision curve analysis was conducted to evaluate the clinical net benefits. …”
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Group-Specific SVM With Bilevel Programming Methods for Parameter Optimization and Explainable AI in Urban Quality of Life Prediction by Gonzalo Rios-Vasquez, Hanns De La Fuente-Mella, Jose Ceroni-Diaz

“…These findings provide valuable insights for policymakers, supporting data-driven decision-making processes for urban development and resource allocation. …”
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Sweet pepper foliar diseases quantification and identification using an image analysis tool by Vijayanandh Rajamanickam, Adesh Ramsubhag, Jayaraj Jayaraman

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Evaluation of health literacy in lung transplant candidates by Jorge Vinales, BS, Rommel Sagana, MD, Kiran H. Lagisetty, MD, Corey Powell, PhD, Jeffrey Clay, ADN, Rebecca Hunt, BSN, Jennifer Shevket, BSN, Vikas Sood, MSN, Ashwin Kulkarni, BS, Krysta Walter, PharmD

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Artificial intelligence in imaging for liver disease diagnosis by Chenglong Yin, Chenglong Yin, Huafeng Zhang, Jin Du, Jin Du, Yingling Zhu, Yingling Zhu, Hua Zhu, Hua Zhu, Hongqin Yue, Hongqin Yue

“…The growing integration of AI into liver imaging is reshaping diagnostic workflows and has the potential to improve accuracy, efficiency, and clinical decision-making. This review provides an overview of AI applications in liver imaging, focusing on their clinical utility and implications for the future of liver disease diagnosis.…”
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Numerical Evaluation of Abdominal Aortic Aneurysms Utilizing Finite Element Method by Konstantinos Kyparissis, Nikolaos Kladovasilakis, Maria-Styliani Daraki, Anastasios Raptis, Polyzois Tsantrizos, Konstantinos Moulakakis, John Kakisis, Christos Manopoulos, Georgios E. Stavroulakis

“…<b>Background:</b> In recent years, more and more numerical tools have been utilized in medicine in or-der to assist the evaluation and decision-making processes for complex clinical cases. …”
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Justifying the selection of a neural network linguistic classifier by Olessia Barkovska, Kseniia Voropaieva, Oleksandr Ruskikh

“…These aspects include classification accuracy, training and prediction time, model size, data distribution, and overall ease of use. By systematically assessing these attributes, this study aims to provide valuable information about the strengths and weaknesses of each model and enable researchers and practitioners to make informed decisions when selecting a neural network classifier for text classification tasks. …”
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RAMAS-Net: a module-optimized convolutional network model for aortic valve stenosis recognition in echocardiography by Yejia Gan, Wanzhong Huang, Yan Deng, Xiaoying Xie, Yuanyuan Gu, Yaozhuang Zhou, Qian Zhang, Maosheng Zhang, Yangchun Liu

“…These results highlight the potential of RSMAS-Net in improving AS assessment and supporting clinical decision-making.…”
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Smart UAV-assisted rose growth monitoring with improved YOLOv10 and Mamba restoration techniques by Fan Zhao, Zhiyan Ren, Jiaqi Wang, Qingyang Wu, Dianhan Xi, Xinlei Shao, Yongying Liu, Yijia Chen, Katsunori Mizuno

“…Our method reduces technical barriers, offering a scalable and cost-effective solution for greenhouse monitoring by addressing low-resolution imagery challenges and enhancing decision-making processes. This research lays the groundwork for broader applications of UAV and AI technologies in sustainable agriculture. …”
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Effectiveness of Radiomics-Based Machine Learning Models in Differentiating Pancreatitis and Pancreatic Ductal Adenocarcinoma: Systematic Review and Meta-Analysis by Lechang Zhang, Dewei Li, Tong Su, Tong Xiao, Shulei Zhao

“…ConclusionsRadiomics-based ML models demonstrate high diagnostic accuracy in differentiating PDAC from MFP, underscoring their potential as noninvasive tools for clinical decision-making. Nonetheless, the overall methodological quality was moderate due to limitations in external validation, standardized protocols, and reproducibility. …”
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Sediment flow connectivity index data for the Apulia region (Italy): An open-source geodatabase and the innovative CONNECTOSED WebGIS platformZenodo by Alok Kushabaha, Domenico Capolongo, Giovanni Scicchitano, Floriana Rizzo, Marina Zingaro

“…The availability of both input and processed data enables the computation and continuous updating of this applied geomorphological indicator, which is useful for assessing susceptibility to rapid Earth surface changes related to multi-hazard exposure. …”
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Artificial Intelligence With Neural Network Algorithms in Pediatric Astrocytoma Diagnosis: A Systematic Review by Floresya K. Farmawati, Della W.A. Nurwakhid, Tifani A. Pradhea, Rayyan Fitriasa, Hutami H. Arrahmi, Muhana F. Ilyas, Fadhilah T. Nur

“…Recent advancements in artificial intelligence (AI), particularly neural network algorithms, have been studied for their precision and efficiency in medical diagnostics via effectively analyzing imaging data to identify patterns and anomalies.Objective: To systematically review AI-based diagnostic tools with neural network algorithms’ methodologies, sensitivities, specificities, and potential clinical integration for pediatric astrocytoma, providing a consolidated perspective on their overall performance and impact on clinical decision-making.Methods: As per PRISMA 2020 guidelines, we conducted a comprehensive search in PubMed, Scopus, and ScienceDirect on February 5, 2024. …”
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Explainable Artificial Intelligence in Radiological Cardiovascular Imaging—A Systematic Review by Matteo Haupt, Martin H. Maurer, Rohit Philip Thomas

“…Explainable Artificial Intelligence (XAI) seeks to address these concerns by providing insights into model decision-making. This systematic review synthesizes current research on the use of XAI methods in radiological cardiovascular imaging. …”
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