Development of machine learning models for the prediction of the skin sensitization potential of cosmetic compounds by Wu Qiao, Tong Xie, Jing Lu, Tinghan Jia

“…Background To enhance the accuracy of allergen detection in cosmetic compounds, we developed a co-culture system that combines HaCaT keratinocytes (transfected with a luciferase plasmid driven by the AKR1C2 promoter) and THP-1 cells for machine learning applications. …”
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Design of the Urban Lighting Control System Based on Optical Multisensor Technology and the GM Model by Weili Wu, Xiang Tang

“…Each road streetlight is equipped with a motion sensor detection device that is tasked with identifying the presence of vehicles and pedestrians within its field of view. …”
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Urban sentinel: advancing structural health monitoring for building damage measurement in districts through IoT integration and self-optimizing machine learning by Parsa Parsafar

“…These sensors transmit data using LoRaWAN wireless technology to a centralized management system, where a regression AI model harnesses the power of machine learning algorithms to analyze the data and predict the health status of the buildings. …”
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Enhancing environmental sustainability and operational efficiency in a case study of limestone quarry in an arid climate by Hussein A. Saleem, Abebe Temesgen Ayalew

“…Automated environmental monitoring systems, incorporating IoT sensors and machine-learning algorithms, provide real-time data on air quality, dust levels, and noise pollution. …”
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Micro-CT Microcalcification Analysis: A Scoping Review of Current Applications and Future Potential in Breast Cancer Research by Redona Brahimetaj, Jan Cornelis, Bart Jansen

“…The studies varied in their purposes: feasibility and optimization of micro-CT for breast cancer imaging and MC analysis/diagnosis, comparison with other imaging modalities, development of micro-CT scanners and processing algorithms, enhancement of MC detection through contrast agents, etc. …”
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An enhanced machine learning approach with stacking ensemble learner for accurate liver cancer diagnosis using feature selection and gene expression data by Amena Mahmoud, Eiko Takaoka

“…The stacking ensemble achieved an accuracy of (97%), outperforming individual machine learning algorithms and traditional diagnostic methods. Furthermore, the model demonstrated high sensitivity (96.8%) and specificity (98.1%), crucial for early detection and minimizing false positives.…”
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A review of ultrasound monitoring applications in agriculture by Muhammad Awais Sattar, Dina Shona Laila

“…Still, recent advances such as improved signal filtering algorithms, new transducer designs, better field sensitivity, and broader collaboration to standardize ultrasound measurement protocols indicate a growing trend toward increased on-field use of ultrasound. …”
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A privacy preserving machine learning framework for medical image analysis using quantized fully connected neural networks with TFHE based inference by Sadhana Selvakumar, B. Senthilkumar

“…Abstract Medical image analysis using deep learning algorithms has become a basis of modern healthcare, enabling early detection, diagnosis, treatment planning, and disease monitoring. …”
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Predicting software reuse using machine learning techniques-A case study on open-source Java software systems. by Matthew Yit Hang Yeow, Chun Yong Chong, Mei Kuan Lim, Yuen Yee Yen

“…This paper proposes automating software reuse prediction by leveraging machine learning (ML) algorithms, enabling future research and practitioners to better identify highly reusable software. …”
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Genomic Variability and Recombination Analysis of Grapevine leafroll-associated virus-1 Isolates from Turkey by Eminur Elçi

“…Furthermore, several putative recombination events were detected with trace to moderate evidence support of algorithms implemented in Recombination Detection Program (RDP). …”
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Deep Learning Automated System for Thermal Defectometry of Multilayer Materials by A. S. Momot, R. M. Galagan, V. Yu. Gluhovskii

“…Three neural network modules are used for automated data processing, each of which performs one of the tasks: defects detection and classification, determination of the defect depth and thickness. …”
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The role of explainable AI in enhancing breast cancer diagnosis using machine learning and deep learning models by Zulfikar Ali Ansari, Manish Madhava Tripathi, Rafeeq Ahmed

“…Although artificial intelligence (AI) has showed amazing promise in breast cancer prediction mainly machine learning (ML) algorithms as well as deep learning (DL), practical use of these models is greatly hampered by their lack of interpretability and transparency. …”
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Rediscovering histology – the application of artificial intelligence in inflammatory bowel disease histologic assessment by Giovanni Santacroce, Irene Zammarchi, Olga Maria Nardone, Ivan Capobianco, Miguel Puga-Tejada, Snehali Majumder, Subrata Ghosh, Marietta Iacucci

“…By leveraging advanced algorithms, AI enhances diagnostic accuracy, reduces assessment variability and streamlines histological workflows in clinical settings. …”
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SHARPNESS IMPROVEMENT OF MAGNETIC RESONANCE IMAGES USING A GUIDED-SUBSUMED UNSHARP MASK FILTER by Manar AL-ABAJI, Zohair AL-AMEEN

“…The GSUM was tested with real-blurry MRI images, evaluated using three no-reference metrics, and compared with six other algorithms. The metric scores indicate that the proposed filter can surpass existing methods, as it produced better results with average readings of 24.2074 in PIQE, 0.6878 in BLUR, and 5.7944 in FISH. …”
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Enhancing semi‐supervised contrastive learning through saliency map for diabetic retinopathy grading by Jiacheng Zhang, Rong Jin, Wenqiang Liu

“…Moreover, the performance of these algorithms is hampered by the scarcity of large‐scale, high‐quality annotated data. …”
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Infections Caused by Carbapenem-Resistant Enterobacterales: Epidemiology, Clinical Significance, and Possibilities for Antibiotic Therapy Optimization by S. V. Yakovlev, M. P. Suvorova, A. O. Bykov

“…Practical issues of management of such patients are discussed. Algorithms for empirical and targeted therapy of infections caused by carbapenem-resistant enterobacteria are presented.…”
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A multi-modality ground-to-air cross-view pose estimation dataset for field robots by Xia Yuan, Kaiyang Wang, Riyu Qin, Jiachen Xu

“…Light Detection And Ranging (LiDAR)-enhanced ground truth further distinguishes its utility for complex outdoor navigation research.…”
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Semi-Supervised Learned Autoencoder for Classification of Events in Distributed Fibre Acoustic Sensors by Artem Kozmin, Oleg Kalashev, Alexey Chernenko, Alexey Redyuk

“…Additionally, advanced signal processing algorithms are necessary for accurately determining the location and nature of detected events. …”
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A Versatile Panel of Reference Gene Assays for the Measurement of Chicken mRNA by Quantitative PCR. by Karen Staines, Ambalika Batra, William Mwangi, Helena J Maier, Steven Van Borm, John R Young, Mark Fife, Colin Butter

“…GeNorm and NormFinder algorithms were able to select appropriate reference gene sets in each case. …”
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PROACTIVE APPROACH IN TAX RISK MANAGEMENT: DATA ANALYSIS TECHNIQUES TO IDENTIFY HIGH-RISK TAXPAYERS by Funda KARAKOYUN

“…While innovations in software programs with digitalisation transformation reduce the manual workload of the tax administration, machine learning algorithms are used with experts employed in the field in continuously developing risk analysis studies. …”
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