Discovery, design, and engineering of enzymes based on molecular retrobiosynthesis by Ancheng Chen, Xiangda Peng, Tao Shen, Liangzhen Zheng, Dong Wu, Sheng Wang

“…We first introduce the molecular retrosynthesis route planning in biochemical pathway design, including single‐step retrosynthesis algorithms and AI‐based chemical retrosynthesis route design tools. …”
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Ischemic Stroke Lesion Segmentation on Multiparametric CT Perfusion Maps Using Deep Neural Network by Ankit Kandpal, Rakesh Kumar Gupta, Anup Singh

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A hybrid approach to time series forecasting: Integrating ARIMA and prophet for improved accuracy by Sherly A, Mary Subaja Christo, Jesi V Elizabeth

“…This research investigates the critical role of time series forecasting within the burgeoning field of edge computing. …”
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Using machine learning for the assessment of ecological status of unmonitored waters in Poland by Andrzej Martyszunis, Małgorzata Loga, Karol Przeździecki

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Bug Wars: Artificial Intelligence Strikes Back in Sepsis Management by Georgios I. Barkas, Ilias E. Dimeas, Ourania S. Kotsiou

“…Key challenges remain regarding data integration, algorithmic bias, and ethical implementation. Future research should prioritize multicenter validation, seamless integration with clinical workflows, and robust ethical frameworks to ensure safe, equitable, and effective adoption. …”
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Machine vision approach for monitoring and quantifying fish school migration by Feng Lin, Jicheng Zhu, Aiju You, Lei Hua

“…Evaluation on an extensive fish migration dataset demonstrates that DVE-YOLO outperforms YOLOv8 and other mainstream detection algorithms, showcasing superior detection accuracy with higher AP50 and AP50−95 metrics. …”
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Stability of the Subaxial Spine after Penetrating Trauma: Do Classification Systems Apply? by Jackson Rucker Staggers, Thomas Elliot Niemeier, William E. Neway, Steven Michael Theiss

“…Blunt spinal trauma classification systems are well established and provide reliable treatment algorithms. To date, stability of the spine after civilian gunshot wounds (CGSWS) is poorly understood. …”
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Experimental determination of factors causing crashes involving automated vehicles by Teshome Kumsa Kurse, Girma Gebresenbet, Geleta Fikadu Daba, Negasa Tesfaye Tefera

“…This study underscores the critical need for enhanced sensor technologies and improved algorithms to better handle adverse weather conditions, complex maneuvers, and varying road and lighting conditions. …”
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Development of a Technique for Discrete-Logical Decision-Making in Medical Information Systems by Islam A. Alexandrov, Vladimir Zh. Kuklin, Leonid M. Chervyakov, Sergei A. Sheptunov

“…The processing and feedforward structures for DSS are presented based on selected types of non-classical logic. The algorithms presented for solving decision-making problems are based on discrete-logic approximations of a priori and actual data, which are optimal or suboptimal, and they use information and value criteria. …”
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Elephant Flows Detection Using Deep Neural Network, Convolutional Neural Network, Long Short-Term Memory, and Autoencoder by Getahun Wassie Geremew, Jianguo Ding

“…Deep autoencoder is also one of the promising algorithms that do not require human class labeler. …”
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Detection of kidney bean leaf spot disease based on a hybrid deep learning model by Yiwei Wang, Qianyu Wang, Yue Su, Binghan Jing, Meichen Feng

“…Based on this dataset, a novel hybrid deep learning model framework is proposed, which integrates deep learning models (EfficientNet-B7, MobileNetV3, ResNet50, and VGG16) for feature extraction with machine learning algorithms (Logistic Regression, Random Forest, AdaBoost, and Stochastic Gradient Boosting) for classification. …”
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Preliminary Study on Sensor-Based Detection of an Adherent Cell’s Pre-Detachment Moment in a MPWM Microfluidic Extraction System by Marius-Alexandru Dinca, Mihaita Nicolae Ardeleanu, Dan Constantin Puchianu, Gabriel Predusca

“…Image processing and deep learning algorithms determine object center coordinates, allowing the MPWM system to dynamically adjust suction parameters. …”
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Estimating Self-Confidence in Video-Based Learning Using Eye-Tracking and Deep Neural Networks by Ankur Bhatt, Ko Watanabe, Jayasankar Santhosh, Andreas Dengel, Shoya Ishimaru

“…The outcomes of this research pave the way for more personalized and effective educational interventions, ultimately contributing to improved learning experiences and outcomes.…”
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Robust Fault Classification in Permanent Magnet Synchronous Machines Under Dynamic and Noisy Conditions by Mikal Laursen, Van-Van Huynh, Duy-Hung Ha, Mahmoud S. Mahmoud, van Khang Huynh

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DEVELOPMENT OF A SOFTWARE MODULE FOR OPERATIONAL DISPATCH CONTROL OF PRODUCTION BASED ON CYBER-PHYSICAL CONTROL SYSTEMS by Igor Nevliudov, Vladyslav Yevsieiev, Nataliia Demska, Sergiy Novoselov

“…The subject of research in the article is production management processes based on cyber-physical systems. …”
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Radiomic Feature Extraction Based on Computed Tomography for Stroke Patients by Alamgir Hossain, Jolly Sultana, Shahed Hossain, Hafizur Rahman

“…To improve diagnosis, classification, and prediction for the best possible patient outcomes, this study investigates how radiomics might improve computed tomography (CT)-based stroke evaluation. Methodology: The research included 65 stroke patients from our two institutions from 2023 to 2024. …”
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Micro-Assembly Error Control of Specialized MEMS Friction Sensor by Wei Zhou, Xiong Wang, Liwei Xue, Huihui Guo, Xiang Qin

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Classification of <i>Verticillium dahliae</i> Vegetative Compatibility Groups (VCGs) with Machine Learning and Hyperspectral Imagery by Sudha GC Upadhaya, Chongyuan Zhang, Sindhuja Sankaran, Timothy Paulitz, David Wheeler

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A Comprehensive Review of Blockchain and Machine Learning Integration for Peer-to-Peer Energy Trading in Smart Grids by Sameen Fatima, Muhammad Junaid Arshad

“…A new architecture is proposed, integrating blockchain with ML algorithms to create resilient, secure, and efficient energy trading markets. …”
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PERFORMANCE COMPARISON OF DECISION TREE AND LOGISTIC REGRESSION METHODS FOR CLASSIFICATION OF SNP GENETIC DATA by Adi Setiawan, Febi Setivani, Tundjung Mahatma

“…This research was conducted to compare the accuracy when decision tree and logistic regression methods are used on some data. …”
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