Large-Scale Maize Condition Mapping to Support Agricultural Risk Management by Edina Birinyi, Dániel Kristóf, Roland Hollós, Zoltán Barcza, Anikó Kern

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Management of drug-induced liver injury associated with anti-cancer therapy by Bruno Vincenzi, Mao Yimin, Raúl J. Andrade, Raúl J. Andrade, Mauricio Morales Castillo, Gamar Akhundova-Unadkat, José M. Mato

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Advancing pancreatic cancer management: the role of artificial intelligence in diagnosis and therapy by Dilber Uzun Ozsahin, Natacha Usanase, Ilker Ozsahin

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A Contextualized Layered Risk Management Framework for Indian Medical Laboratories by Yogesh R Pawade, Anita S Chalak, Hemant S Dahake

“…Introduction: Medical laboratories are indispensable to modern health care; yet their operations inherently involve risks that can undermine quality and safety if not effectively managed. …”
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Emerging Applications for Computer Vision and Artificial Intelligence in Management of the Cardiovascular Patient by Peter Osztrogonacz, Ponraj Chinnadurai, Alan B. Lumsden

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Real-Time Detection and Process Status Integration System for High-Pressure Gas Leakage by Nian-Ze Hu, Hao-Lun Huang, Chun-Min Tsai, Yen-Yu Wu, You-Xin Lin, Chih-Chen Lin, Po-Han Lu

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Early Prediction Detection of Retail and Corporate Credit Risks Using Machine Learning Algorithms by Mohamed A. Hamada, Karim Farag, Adejor E. Abiche

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Design of a Transformer-GRU-Based Satellite Power System Status Detection Algorithm by Guoqi Xie, Xinhao Yang, Jiayu Zhao, Zhou Huang

“…The health state of satellite power systems plays a critical role in ensuring the normal operation of satellite platforms. This paper proposes an improved Transformer-GRU-based algorithm for satellite power status detection, which characterizes the operational condition of power systems by utilizing voltage and temperature data from battery packs. …”
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Optimizing survey conditions for Burmese python detection and removal using community science data by Kelly R. McCaffrey, Melissa A. Miller, Sergio A. Balaguera-Reina, Alexander S. Romer, Michael Kirkland, Amy Peters, Edward F. Metzger, LeRoy Rodgers, Frank J. Mazzotti

“…We examined data from South Florida Water Management District’s Python Elimination Program to determine the effect of operational and environmental covariates on two measures of survey outcome: success (i.e., probability of removing at least one python) and efficiency (i.e., the number of pythons removed per survey hour). …”
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Business Logic Vulnerabilities in the Digital Era: A Detection Framework Using Artificial Intelligence by Bilgin Metin, Martin Wynn, Aylin Tunalı, Yağmur Kepir

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Anaesthetic Management for Patient with Trigeminal Neuralgia underwent Microvascular Decompression (MVD) by Rapto Hardian, Edwin Pratama, Dwi Septwo Rustaminta Tarigan, Kenanga Marwan Sikumbang

“…Early emergence with smooth extubation to prevent sudden haemodynamic changes and minimising coughing then for early neurological detection of intracranial complications.The combined use of sevoflurane < 1MAC and continuous propofol provides optimal visualisation of the operating area. …”
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Functional Nanomaterials for Advanced Bioelectrode Interfaces: Recent Advances in Disease Detection and Metabolic Monitoring by Junlong Ma, Siyi Yang, Zhihao Yang, Ziliang He, Zhanhong Du

“…Furthermore, this work focused on persistent technical challenges regarding nanomaterial biocompatibility and long-term operational stability while providing forward-looking perspectives on their translational applications in wearable medical devices and personalized health management systems. …”
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Artificial Intelligence and Internet of Things-Based Leak Detection Method for the Water Supply Network by Lianxiu Li, Huifan Chen

“…The good management and safe operation of the urban water supply network are of great significance to residents’ lives and industrial production. …”
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Real-Time Power System Event Detection: A Novel Instance Selection Approach by Gabriel Intriago, Yu Zhang

“…Wide-area monitoring, protection, and control (WAMPAC) systems allow system operators to operate CPPS more efficiently and reliably. …”
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Evaluating Pipeline Inspection Technologies for Enhanced Corrosion Detection in Mining Water Transport Systems by Víctor Tuninetti, Matías Huentemilla, Álvaro Gómez, Angelo Oñate, Brahim Menacer, Sunny Narayan, Cristóbal Montalba

“…A structured methodology combining diagnostic assessment, technology research, and comparative evaluation was applied, using key performance indicators like detection capability, operational impact, and feasibility. …”
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A lightweight remote sensing image detection model with feature aggregation diffusion network by Xiaohui Cheng, Xukun Wang, Yun Deng, Qiu Lu, Yanping Kang, Jian Tang, Yuanyuan Shi, Junyu Zhao

“…Evaluated on benchmark datasets, LightFAD-YOLO achieves 1.7 % higher mAP0.5 and 6.4 % improved mAP0.5:0.95 over baseline models, with 9.9 % lower computational load. Operating at 297.2 FPS with only 2.3M parameters, it enables real-time deployment on edge devices for land-use monitoring and infrastructure detection, supporting sustainable land management.…”
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Geospatial Segmentation and Vision AI for Rapid Detection and Classification of Faults in Rooftop Solar Panels by Tientanopajai Kitt, Khuanmar Kulyakorn, Kanarkard Wanida

“…By accurately segmenting and assessing solar panels, the proposed method delivers detailed insights into damage detection, optimal panel placement, and streamlined lifecycle management processes for photovoltaic installations, ultimately contributing to improved energy production and operational efficiency.…”
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Research on anomaly detection model for traffic time series data integrating multiple mechanisms by Peipei ZHANG, Jiaqi LIU

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Outlier Detection and Correction in Smart Grid Energy Demand Data Using Sparse Autoencoders by Levi da Costa Pimentel, Ricardo Wagner Correia Guerra Filho, Juan Moises Mauricio Villanueva, Yuri Percy Molina Rodriguez

“…The results provide an overview of the operation as well as demonstrate the effectiveness of the proposed methodology that manages to improve some indices achieved by previous works, reaching accuracy and F-score superior to 99% and 97%, respectively, for the detection algorithm, as well as a square root mean squared error (RMSE) and a mean absolute percentage error (MAPE) of less than 0.2 MW and 2%, respectively.…”
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Deep Learning-Based Anomaly Detection in Occupational Accident Data Using Fractional Dimensions by Ömer Akgüller, Larissa M. Batrancea, Mehmet Ali Balcı, Gökhan Tuna, Anca Nichita

“…The results demonstrate that the VAE model consistently detects a broader range of anomalies, particularly in sectors with complex operational processes like NACE05 and NACE30. …”
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