Hybrid machine learning algorithms accurately predict marine ecological communities by Luciana Erika Yaginuma, Luciana Erika Yaginuma, Fabiane Gallucci, Danilo Cândido Vieira, Paula Foltran Gheller, Simone Brito de Jesus, Thais Navajas Corbisier, Gustavo Fonseca

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X-FuseRLSTM: A Cross-Domain Explainable Intrusion Detection Framework in IoT Using the Attention-Guided Dual-Path Feature Fusion and Residual LSTM by Adel Alabbadi, Fuad Bajaber

“…Due to domain variability and developing attack tactics, intrusion detection in heterogeneous and dynamic IoT systems is still a crucial challenge. …”
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Rose-Mamba-YOLO: an enhanced framework for efficient and accurate greenhouse rose monitoring by Sicheng You, Boheng Li, Yijia Chen, Zhiyan Ren, Yongying Liu, Qingyang Wu, Jianghan Tao, Zhijie Zhang, Chenyu Zhang, Feng Xue, Yulun Chen, Guochen Zhang, Jundong Chen, Jiaqi Wang, Fan Zhao

“…Accurately detecting roses in UAV-captured greenhouse imagery presents significant challenges due to occlusions, scale variability, and complex environmental conditions. …”
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Anomaly Detection and Root Cause Analysis for Energy Consumption of Medium and Heavy Plate: A Novel Method Based on Bayesian Neural Network with Adam Variational Inference by Qiang Guo, Fenghe Li, Hengwen Liu, Jin Guo

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Emerging Healthcare Technologies in Gastrointestinal Endoscopy: 75 Years of Evolution by Irina Florina CHERCIU HARBIYELI, Elena Daniela BURTEA, Vlad IOVANESCU, Dan Nicolae FLORESCU, Ion ROGOVEANU, Dan Ionut GHEONEA, Adrian SAFTOIU

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Prediction of the packaging chemical migration into food and water by cutting-edge machine learning techniques by Behzad Vaferi, Mohsen Dehbashi, Reza Yousefzadeh, Ali Hosin Alibak

“…Due to the costly and time-intensive nature of experimental measurements, employing artificial intelligence (AI) methodologies is beneficial. This research uses five renowned AI-based techniques (namely, long short-term memory, gradient boosting regressor, multi-layer perceptron, Random Forest, and convolutional neural networks) to anticipate chemical migration from packaging materials to the food/water structure, considering variables such as temperature, chemical characteristics, and packaging/food types. …”
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Prediction of bloodstream infection using machine learning based primarily on biochemical data by Ramtin Zargari Marandi, Frederik Boetius Hertz, Jesper Qvist Thomassen, Steen Christian Rasmussen, Ruth Frikke-Schmidt, Niels Frimodt-Møller, Karen Leth Nielsen, Cameron Ross MacPherson

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Disc Diffusion Reader: an AI-powered potential solution to combat antibiotic resistance in developing countries by Hoang B Nguyen, Thanh L Phan, Thi T Ung, Thi KL Nguyen

“…Methodology: Images of Kirby-Bauer test results were annotated to train the Faster R-CNN ResNet-50 to detect agar plates, inhibition zones, and antibiotic discs. …”
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Comparative analysis of convolutional neural networks and transformer architectures for breast cancer histopathological image classification by Bo Yuan, Yudie Hu, Yan Liang, Yutong Zhu, Lingyu Zhang, Shimin Cai, Rui Peng, Xianbin Wang, Zheng Yang, Jinhui Hu

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Revolutionizing Sports: The Role of Wearable Technology and AI in Training and Performance Analysis by Stanisław Dudek, Weronika Koziak, Michalina Makieła, Aleksandra Bętkowska, Agata Kornacka, Wojciech Dudek, Kamila Szostak, Rafał Tomaka, Anna Byra

“… The integration of wearable technology and artificial intelligence (AI) has transformed modern sports science by enhancing athlete monitoring, performance optimization, and injury prevention. …”
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Deep learning for retinal non-perfusion and foveal avascular zone analysis in wide-field OCTA in diabetic retinopathy by Hugo Le Boité, Sophie Bonnin, Mathias Gallardo, Mathieu Lamard, Aude Couturier, Gwenolé Quellec

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Large language models in medical education: a comparative cross-platform evaluation in answering histological questions by Volodymyr Mavrych, Einas M. Yousef, Ahmed Yaqinuddin, Olena Bolgova

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Understanding Flaky Tests Through Linguistic Diversity: A Cross-Language and Comparative Machine Learning Study by Azeem Ahmad, Xin Sun, Muhammad Rashid Naeem, Yasir Javed, Mohammad Akour, Kristian Sandahl

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Technological Progress Toward Peanut Disease Management: A Review by Muhammad Asif, Aleena Rayamajhi, Md Sultan Mahmud

“…These advancements include the use of various platforms, such as ground-based and unmanned aerial vehicle (UAV)-based systems, equipped with sensors like RGB (red–blue–green), multispectral, thermal, hyperspectral, light detection and ranging (LiDAR), and other innovative detection technologies, as highlighted in this review. …”
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Interpreting Temporal Shifts in Global Annual Data Using Local Surrogate Models by Shou Nakano, Yang Liu

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Automatic Weight-Bearing Foot Series Measurements Using Deep Learning by Jordan Tanzilli, Alexandre Parpaleix, Fabien de Oliveira, Mohamed Ali Chaouch, Maxime Tardieu, Malo Huard, Aymeric Guibal

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Soil Temperature Prediction via Self-Training: Izmir Case by Göksu Tüysüzoğlu, Derya Birant, Volkan Kıranoglu

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A Computer-Aided Approach to Canine Hip Dysplasia Assessment: Measuring Femoral Head–Acetabulum Distance with Deep Learning by Pedro Franco-Gonçalo, Pedro Leite, Sofia Alves-Pimenta, Bruno Colaço, Lio Gonçalves, Vítor Filipe, Fintan McEvoy, Manuel Ferreira, Mário Ginja

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Harnessing AI-Powered Genomic Research for Sustainable Crop Improvement by Elżbieta Wójcik-Gront, Bartłomiej Zieniuk, Magdalena Pawełkowicz

“…Artificial intelligence (AI) can revolutionize agriculture by enhancing genomic research and promoting sustainable crop improvement. …”
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Resilient AI in Therapeutic Rehabilitation: The Integration of Computer Vision and Deep Learning for Dynamic Therapy Adaptation by Egidia Cirillo, Claudia Conte, Alberto Moccardi, Mattia Fonisto

“…The main objective is to develop an intelligent system that captures and analyzes a patient’s movements in real time using Motion Capture techniques and artificial intelligence (AI) models to improve the effectiveness of therapies. …”
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