Can Synthetic Data Allow for Smaller Sample Sizes in Chronic Urticaria Research? by Annika Gutsche, Pascale Salameh, Samad S. Jahandideh, Mehran Roodsaz, Serkan Kutan, Ali Salehzadeh‐Yazdi, Emek Kocatürk, Stamatios Gregoriou, Simon F. Thomsen, Kanokvalai Kulthanan, Papapit Tuchinda, Joachim Dissemond, Alicja Kasperska‐Zajac, Magdalena Zajac, Mateusz Zamłyński, Martijn vanDoorn, Claudio A. S. Parisi, Jonny G. Peter, Cascia Day, Cathryn McDougall, Michael Makris, Daria Fomina, Elena Kovalkova, Nikolai Streliaev, Gerelma Andrenova, Marina Lebedkina, Maryam Khoskhkui, Mehraneh M. Aliabadi, Andrea Bauer, Lea Kiefer, Melba Muñoz, Karsten Weller, Pavel Kolkhir, Martin Metz

“…The lowest threshold at which synthetic data could be generated while maintaining high accuracy in RWD was identified to be 25%, enabling a fourfold increase in the synthetic population. …”
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AI-based pelvic floor surface electromyography reference ranges and high-precision pelvic floor dysfunction diagnosisResearch in context by Juan Chen, Jiahui Yao, Wei Chen, Feng Zhang, Heyuan Wang, Xiaoying Xu, Huan Ge, Hongmei Zhou, Jin Cen, Dan Li, Bengui Jiang, Li He, Tingting Fu, Zhengxian Xu, Lei Chu, Shuxia Zhang, Dongmei Yao, Linyi Wei, Liu Huang, Anjing Ge, Cuiping Jin, Zimu Fu, Qin Liu, Xuefeng Yu, Chengmao Zhao, Tengjiao Wang, Lan Zhu

“…Data from 15 centres were divided into a training dataset (60%) and a test dataset (40%), while data from 6 additional centres were used to form an independent validation dataset. …”
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An accuracy-privacy optimization framework considering user’s privacy requirements for data stream mining by Waruni Hewage, R. Sinha, M. Asif Naeem

“…Consequently, preserving the privacy of sensitive information while maintaining high accuracy remains a persistent challenge. …”
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A hybrid optimization-enhanced 1D-ResCNN framework for epileptic spike detection in scalp EEG signals by Priyaranjan Kumar, Prabhat Kumar Upadhyay

“…The Layer-wise Adaptive Moments (LAMB) and AdamW algorithms have been used in the model’s optimization to improve efficiency and accelerate convergence while extracting features from time and frequency domain EEG data. …”
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A Systematic Review of CNN Architectures, Databases, Performance Metrics, and Applications in Face Recognition by Andisani Nemavhola, Colin Chibaya, Serestina Viriri

“…Overall, the findings emphasize the need for advanced algorithms capable of handling large-scale, real-world challenges while optimizing accuracy and computational efficiency in face recognition systems.…”
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Enhancing Coverage and Efficiency in Wireless Sensor Networks: A Review of Optimization Techniques by Rajasekaran S, Shaik Mastan Vali

“…Key findings emphasize the effectiveness of various techniques in enhancing coverage, such as mobility-based approaches and energy-aware algorithms, while also addressing practical challenges like sensor redundancy and environmental unpredictability. …”
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An efficient interpretable framework for unsupervised low, very low and extreme birth weight detection. by Ali Nawaz, Amir Ahmad, Shehroz S Khan, Mohammad Mehedy Masud, Nadirah Ghenimi, Luai A Ahmed

“…The OCSVM attained an AUCROC of 0.72 and an AUCPR of 0.0253 for extreme LBW detection, while the ECOD model showed competitive performance with an AUCPR of 0.045 for very low LBW cases. …”
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OWNC: Open-World Node Classification on Graphs with a Dual-Embedding Interaction Framework by Yuli Chen, Chun Wang

“…Experimental results on three benchmark datasets demonstrate the superior performance of our model compared to various baseline algorithms, while ablation studies validate the underlying mechanisms and robustness of our approach.…”
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Artificial Intelligence for the Evaluation of Postures Using Radar Technology: A Case Study by Davide De Vittorio, Antonio Barili, Giovanni Danese, Elisa Marenzi

“…Monitoring devices based on radar sensors represent a possible approach to tackle postural analysis while preserving the person’s privacy and are especially useful in domestic environments. …”
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Introduction to the Special Thematic Issue "Virtual Reality and Eye Tracking" by Béatrice Hasler, Rudolf Groner

“…Many new VR/AR headsets already include eye tracking as a standard feature. While its application previously has been mostly limited to research, we now see installations of eye tracking into consumer level VR products in entertainment, training, and therapy.  …”
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Explicit and Implicit Knowledge in Large-Scale Linguistic Data and Digital Footprints from Social Networks by Maria Pilgun

“…This research aims to develop and test algorithms for analyzing both explicit and implicit information in user-generated content and digital interactions. …”
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Artificial intelligence-augmented smart grid architecture for cyber intrusion detection and mitigation in electric vehicle charging infrastructure by Ankita Sharma, Shalli Rani, Mohammad Shabaz

“…Abstract The role of electric vehicles (EV) is crucial in the shift toward sustainable transportation while reducing greenhouse gas emissions. However, integrating EVs into smart grids introduces significant cybersecurity and operational challenges. …”
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Development of a Drought Monitoring System for Winter Wheat in the Huang-Huai-Hai Region, China, Utilizing a Machine Learning–Physical Process Hybrid Model by Qianchuan Mi, Zhiguo Huo, Meixuan Li, Lei Zhang, Rui Kong, Fengyin Zhang, Yi Wang, Yuxin Huo

“…The existing simulation methods like physical process models and machine learning (ML) algorithms have limitations: physical models struggle with parameter acquisition at regional scales, while ML algorithms face difficulties in agricultural settings due to the presence of crops. …”
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A simplification method for large-scale urban point clouds considering diversity of terrain object features by Shen Shen, Yonghong Wu, Hongwei Zhang, Jiankai Lu, Hong Fan

“…Existing 3D point cloud simplification algorithms predominantly focus on simple point cloud objects and often fail to support large-scale data processing while preserving diverse geometric features. …”
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Interacting Large Language Model Agents. Bayesian Social Learning Based Interpretable Models by Adit Jain, Vikram Krishnamurthy

“…This paper discusses the theory and algorithms for interacting large language model agents (LLMAs) using methods from statistical signal processing and microeconomics. …”
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Artificial intelligence: Applications in cardio-oncology and potential impact on racial disparities by Gift Echefu, Rushabh Shah, Zanele Sanchez, John Rickards, Sherry-Ann Brown

“…In this review, we explore the impact of AI on cardio-oncology care, particularly regarding predicting cardiotoxicity from cancer treatments, while addressing racial and ethnic biases in algorithmic implementation.…”
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Explainable light-weight deep learning pipeline for improved drought stress identification by Aswini Kumar Patra, Aswini Kumar Patra, Lingaraj Sahoo

“…While these approaches yield favorable results, real-time field applications require algorithms specifically designed for the complexities of natural agricultural conditions.MethodsOur work proposes a novel deep learning framework for classifying drought stress in potato crops captured by unmanned aerial vehicles (UAV) in natural settings. …”
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Integrating data-driven and physics-based approaches for robust wind power prediction: A comprehensive ML-PINN-Simulink framework by Rajaperumal T. A, Christopher Columbus Chinnappan

“…Abstract This study presents a comprehensive hybrid forecasting framework that synergizes machine learning algorithms, MATLAB Simulink-based physical modeling, and Physics-Informed Neural Networks (PINNs) to advance wind power prediction accuracy for a 10 kW Permanent Magnet Synchronous Generator (PMSG)-based Wind Energy Conversion System (WECS). …”
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Methodical Approaches to Creation of Dividing Automation at Industrial Enterprises with Generating Power Plants by E. V. Kalentionok, Y. D. Filipchik

“…The paper considers a problem pertaining to creation of dividing automation at industrial enterprises which have their own generating plants. Algorithms for action of dividing automation that permit to ensure minimum possible power non-balance while using generating plants for autonomous operation and possible parameters for its response are proposed in the paper.…”
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Real-space heterogeneous reconstruction, refinement, and disentanglement of CryoEM conformational states with HetSIREN by David Herreros, Carlos Perez Mata, Chari Noddings, Deli Irene, James Krieger, David A. Agard, Ming-Daw Tsai, Carlos Oscar Sanchez Sorzano, Jose Maria Carazo

“…Traditional methods assume discrete conformations, while newer algorithms estimate conformational landscapes representing the different structural states a biomolecule explores. …”
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