Dysregulation of innate and adaptive lymphoid immunity may have implications for symptom attribution and predict responses to targeted therapies in neuropsychiatric systemic lupus... by Julius Lindblom, Guillermo Barturen, Lorenzo Beretta, Daniel Toro-Domínguez, Elena Carnero-Montoro, Maria Orietta Borghi, Jessica Castillo, Ellen Iacobaeus, Yvonne Enman, Chandra Mohan, Marta E. Alarcón-Riquelme, Dionysis Nikolopoulos, Ioannis Parodis, Jacques-Olivier Pers, Alain Saraux, Valérie Devauchelle-Pensec, Sandrine Jousse-Joulin, Bernard Lauwerys, Julie Ducreux, Anne-Lise Maudoux, Ana Tavares, Isabel Almeida, Miguel Angel Gonzalez-Gay Mantecón, Ricardo Blanco Alonso, Alfonso Corrales Martínez, Ignasi Rodríguez-Pintó, Gerard Espinosa, Rik Lories, Nicolas Hunzelmann, Doreen Belz, Niklas Baerlecken, Michael Zauner, Michaela Lehner, Eduardo Collantes, Ma Angeles Aguirre-Zamorano, Alejandro Escudero-Contreras, Ma Carmen Castro-Villegas, Norberto Ortego, María Concepción Fernández Roldán, Enrique Raya, Inmaculada Jiménez Moleón, Enrique de Ramon, Isabel Díaz Quintero, Pier Luigi Meroni, Tommaso Schioppo, Carolina Artusi, Carlo Chizzolini, Aleksandra Zuber, Donatienne Wynar, Attila Balog, Magdolna Deák, Márta Bocskai, Sonja Dulic, Gabriella Kádár, Falk Hiepe, Silvia Thiel, Manuel Rodriguez Maresca, Antonio López-Berrio, Rocío Aguilar-Quesada, Héctor Navarro-Linares

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CORE-MD clinical risk score for regulatory evaluation of artificial intelligence-based medical device software by Frank E. Rademakers, Elisabetta Biasin, Nico Bruining, Enrico G. Caiani, Rhodri H. Davies, Stephen H. Gilbert, Eric Kamenjasevic, Gearóid McGauran, Gearóid O’Connor, Jean-Baptiste Rouffet, Baptiste Vasey, Alan G. Fraser

“…Abstract The European CORE–MD consortium (Coordinating Research and Evidence for Medical Devices) proposes a score for medical devices incorporating artificial intelligence or machine learning algorithms. …”
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Hyperspectral estimation of chlorophyll density in winter wheat using fractional-order derivative combined with machine learning by Chenbo Yang, Chenbo Yang, Meichen Feng, Juan Bai, Hui Sun, Rutian Bi, Lifang Song, Chao Wang, Yu Zhao, Wude Yang, Lujie Xiao, Meijun Zhang, Xiaoyan Song

“…Caputo-FOD was not suitable for hyperspectral research due to its insensitivity to changes in order. …”
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Examining the Role of Social Media in New Social Movements A Case Study of the Black Lives Matter Movement by Ali Davari, Mostafa Ghaffari

“…The findings suggest that future research should adapt Melucci’s framework to address contemporary challenges such as platform governance, algorithmic amplification, and activist burnout in digital environments. …”
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Prediksi Kesiapan Sekolah Menggunakan Machine Learning Berbasis Kombinasi Adam dan Nesterov Momentum by Indah Mustika Rahayu, Ahmad Yusuf, Mujib Ridwan

“…Based on the Chi-Square correlation, variables that have a strong significant relationship to school readiness test results are pre-elementary status, number of siblings and age with p<.05. The research used Artificial Neural Network algorithms with a combination of Adam and Nesterov Momentum optimization method. …”
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From Culture-Negative to DNA-Positive: The Molecular Revolution in Infective Endocarditis Diagnosis by Myeongji Kim, Madiha Fida, Omar M. Abu Saleh, Nischal Ranganath

“…A multimodal approach integrating molecular diagnostics with conventional methods is essential to optimize patient management. Further research is needed to refine diagnostic algorithms and improve cost-effectiveness in clinical practice.…”
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Efficient Air Quality Prediction Models Based on Supervised Machine Learning Techniques by Oumoulylte Mariame, El Allaoui Ahmad, Farhaoui Yousef, Boughrous Ali Ait

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Adapting e-Genius for Next-Level Efficient Electric Aerotow with High-Power Propulsion and Automatic Flight Control System by Stefan Zistler, Dalong Shi, Walter Fichter, Andreas Strohmayer

“…Aiming to reduce energy demand and carbon footprint, minimize noise impact, and enhance flight safety and efficiency during aerotow operations, this study integrates an electric propulsion system and an automatic flight control system (AFCS) into the electric research aircraft e-Genius. An advanced propulsion system is developed using high-performance batteries and available electric drive components, while the AFCS is designed following a systematic process of developing flight control algorithms. …”
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Optimization and predictive modelling for the diameter of nylon-6,6 nanofibers via electrospinning for coronavirus face masks by Malihe Zeraati, Rana Pourmohamad, Bahareh Baghchi, Narendra Pal Singh Chauhan, Ghasem Sargazi

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Enhanced leukemia prediction using hybrid ant colony and ant lion optimization for gene selection and classification by Santhakumar D, Gnanajeyaraman Rajaram, Elankavi R, Viswanath J, Govindharaj I, Raja J

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Machine Learning Models in the Detection of MB2 Canal Orifice in CBCT Images by Shishir Shetty, Meliz Yuvali, Ilker Ozsahin, Saad Al-Bayatti, Sangeetha Narasimhan, Mohammed Alsaegh, Hiba Al-Daghestani, Raghavendra Shetty, Renita Castelino, Leena R David, Dilber Uzun Ozsahin

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Non-invasive ML methods for diagnosis of congenital heart disease associated with pulmonary arterial hypertension by Yuyang Gao, Pengyue Ma, Jiahua Pan, Hongbo Yang, Tao Guo, Weilian Wang

“…In the classification phase, considering the lack of CHD-PAH data, ensemble learning was widely used.Main resultsAn accuracy of 88.61% was achieved with direct three-divided model and 90.9% with two-stage classification model.SignificanceBy analyzing and discussing these algorithms, future research directions of CHD-PAH assisted diagnosis were discussed. …”
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Motion Cancellation Technique of Vital Signal Detectors Based on Continuous-Wave Radar Technology by Min-Seok Kwon, Yuna Park, Joo-Eun Park, Geon-Haeng Lee, Sang-Hoon Jeon, Jae-Hyun Lee, Joon-Hyuk Yoon, Jong-Ryul Yang

“…The various motion cancellation techniques that have been proposed to enhance robustness against RBMs include improvements in radar architecture, advanced signal processing algorithms, and studies on electromagnetic propagation characteristics. …”
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Traumatic Brain Injury and Artificial Intelligence: Shaping the Future of Neurorehabilitation—A Review by Seun Orenuga, Philip Jordache, Daniel Mirzai, Tyler Monteros, Ernesto Gonzalez, Ahmed Madkoor, Rahim Hirani, Raj K. Tiwari, Mill Etienne

“…Despite these advances, ethical considerations, including biases in AI algorithms and data generalizability, pose challenges that must be addressed to optimize AI’s implementation in clinical settings. …”
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Reward shaping-based deep reinforcement learning for look-ahead dispatch with rolling-horizon by Hongsheng Xu, Yungui Xu, Ke Wang, Yaping Li, Abdullah Al Ahad

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UNS Geo: LiDAR Dataset for point cloud classification in urban areas by M. Govedarica, G. Jakovljevic, I. Ruskoviski, V. Pajic

“…Although in the last few years, different methodologies and algorithms have been proposed, precise and detailed point cloud labelling is still challenging. …”
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Deep Learning-Based Cloud Detection for Optical Remote Sensing Images: A Survey by Zhengxin Wang, Longlong Zhao, Jintao Meng, Yu Han, Xiaoli Li, Ruixia Jiang, Jinsong Chen, Hongzhong Li

“…This review provides a comprehensive overview of cloud detection algorithms based on deep learning from the perspective of semantic segmentation, and elaborates on the research progress, advantages, and limitations of different categories in this field. …”
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A review on machine learning applications in hydrogen energy systems by Zaid Allal, Hassan N. Noura, Ola Salman, Flavien Vernier, Khaled Chahine

“…The paper provides an in-depth review of the literature, examining not only ML techniques but also optimization algorithms, evaluation methods, explainability techniques, and emerging technologies. …”
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Parallel Multi-Scale Semantic-Depth Interactive Fusion Network for Depth Estimation by Chenchen Fu, Sujunjie Sun, Ning Wei, Vincent Chau, Xueyong Xu, Weiwei Wu

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Application of Feedforward Artificial Neural Networks to Predict the Hydraulic State of a Water Distribution Network by Leandro Evangelista, Débora Móller, Bruno Brentan, Gustavo Meirelles

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