Individualized post‐operative prediction of cochlear implantation outcomes in children with prelingual deafness using functional near‐infrared spectroscopy by Zhe Chen, Xue Zhao, Haotian Liu, Yuyang Wang, Zhikai Zhang, Yuxuan Zhang, Yuhe Liu

“…Both classification and individualized regression models were constructed to predict post‐CI behavioral improvement from fNIRS data using support vector machine (SVM) learning algorithms. …”
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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

“…This literature review explores the current and potential applications of AI in TBI management, focusing on AI’s role in diagnostic tools, neuroimaging, prognostic modeling, and rehabilitation programs. AI-driven algorithms have demonstrated high accuracy in predicting mortality, functional outcomes, and personalized rehabilitation strategies based on patient data. …”
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Recent Results on the Use of Artificial Intelligence Techniques Applied to Wireless Power Transfer Systems by Federico Amadei, Michele Quercio, Francesco Riganti Fulginei

“…The article discusses various approaches, including supervised learning, regression models, and Q-learning algorithms, highlighting their ability to reduce design time, improving system efficiency, and mitigate risks associated with misalignment and object interference. …”
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Automated segmentation of brain metastases in T1-weighted contrast-enhanced MR images pre and post stereotactic radiosurgery by Hemalatha Kanakarajan, Wouter De Baene, Patrick Hanssens, Margriet Sitskoorn

“…Previous studies assessed several DL algorithms focusing only on training and testing the models on the planning MRI only. …”
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Software and methodological support for additional professional courses: ideas, problems, monitoring by O. D. Prokhorenko, S. V. Morin, O. A. Kozyreva

“…By building prospects for theorizing and implementing ideas for improving the quality of modeling and using software and methodological support for further education courses, we can distinguish in the integrative representation of the direction and prospects of an individual’s achievements three types of solving professional and pedagogical problems theorized in the work (algorithmic, creative-stimulative and innovative-promising).…”
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Continuum Robots: Current Trends in Design, Control, and Applications by Marina Kalekeyeva, Zarina Konakbay, Meiramgul Imanbekova, Aliya Shakbutova, Olga Garmash, Gulzhan Muratbekova, Doszhan Mambetalin

“…Despite promising achievements, the processes of design, modeling, control system development, and improvement of existing CR mechanisms remain quite complex. …”
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Recursive GNNs for Learning Precoding Policies With Size-Generalizability by Jia Guo, Chenyang Yang

“…Nonetheless, it has been noticed in literature that only satisfying the PE property of a precoding policy in multi-antenna systems cannot ensure a GNN for learning precoding to be generalizable to the unseen problem scales. Incorporating models with GNNs helps improve size generalizability, which however is only applicable to specific problems, settings, and algorithms. …”
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Breaks in the Arctic ice cover: from observations to predictions by A. A. Ershova, L. N. Dyment, T. A. Alekseeva

“…Such information is needed for solving problems of improving models of ice cover dynamics and modeling the interaction between the ocean and the atmosphere at high latitudes. …”
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Integrating machine learning and sentiment analysis in movie recommendation systems by Amany M. Sarhan, Hager Ayman, Mariam Wagdi, Bassant Ali, Aliaa Adel, Rahf Osama

“…Abstract The fast growth of the film business, along with an ever-increasing number of movie options, has highlighted the need for better recommendation algorithms. This study investigates the application of sentiment analysis in a movie recommendation system with the goal of improving the user experience. …”
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A beginner’s approach to deep learning applied to VS and MD techniques by Stijn D’Hondt, José Oramas, Hans De Winter

“…This review focusses on a survey of recent applications of DL in molecular modelling techniques. The different sections are logically subdivided, based on where DL is integrated in the research: (1) for the improvement of VS workflows, (2) for the improvement of certain workflows in MD simulations, (3) for aiding in the calculations of interatomic forces, or (4) for data analysis of MD trajectories. …”
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Resource allocation mechanism in the TWDM-PON and C-RAN joint architecture with hybrid energy supply by Ruyan WANG, Ningning XU

“…Aiming at the problems of low resource utilization rate,high energy consumption and poor user service quality in the existing virtualized Cloud Radio Access Network,an energy-aware virtualized resource allocation mechanism with hybrid energy supply was proposed.According to the energy sources and energy consumption of different network devices,energy arrival and energy consumption models were established.Furthermore,under the premise of guaranteeing the quality of user services,considering proportional fairness and energy consumption optimization,distributed algorithms based on asynchronous update were used to allocate resources and harvested energy for different types of virtual cloud radio access networks and user virtual base stations to effectively improve the energy efficiency of network.The simulation results show that the proposed resource allocation mechanism can reduce energy consumption while effectively reducing the latency and improving the throughput.…”
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Enhancing Breast Cancer Diagnosis With Multi-Resolution Vision Transformers and Robust Decision-Making by Margo Sabry, Hossam Magdy Balaha, Khadiga M. Ali, Tayseer Hassan A. Soliman, Dibson Gondim, Mohammed Ghazal, Norah Saleh Alghamdi, Ayman El-Baz

“…A stacking ensemble method combines predictions from ViT models trained at these levels, improving classification robustness. …”
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How Recent Findings in Electromyographic Analysis and Synergistic Control Can Impact on New Directions for Muscle Synergy Assessment in Sports by Alessandro Scano, Valentina Lanzani, Cristina Brambilla

“…We identified several margins for improvement, which include novel models and updated algorithms: the separation of the EMG components (phasic and tonic) leading repertoires of synergies for motion and holding posture; the choice of multiple synergistic models (spatial/temporal/time-varying and others); the connection of synergies with the task space and the consequent role of non-linearities; the use of computational models and digital twins; and the fields and sports in which synergies can be applied. …”
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ILSTMA: Enhancing Accuracy and Speed of Long-Term and Short-Term Memory Architecture by Zongyu Ming, Zimu Wu, Genlang Chen

“…Furthermore, our proposed most relevant dialogue retrieval process substantially enhances the answer accuracy of LLMs while examining the potential of the two most commonly used memory retrieval algorithms. Experimental results demonstrate that our acceleration method improves the execution efficiency of the original architecture by 21.45%, and our most relevant dialogue retrieval process raises the answer accuracy to 88.4%, surpassing several benchmarks. …”
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Unmasking social bots: how confident are we? by James Giroux, Gangani Ariyarathne, Alexander C. Nwala, Cristiano Fanelli

“…Despite the progress made in developing multiple sophisticated social bot detection algorithms and tools, bot detection remains a challenging, unsolved problem that is fraught with uncertainty due to the heterogeneity of bot behaviors, training data, and detection algorithms. …”
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Automated epidermal thickness quantification of in vitro human skin equivalents using optical coherence tomography by Martina M Sanchez, Danielle N Orneles, B Hyle Park, Joshua T Morgan

“…The techniques presented here demonstrate the use of OCT imaging to track HSE epidermal thickness over 8 weeks of culture and improve upon previous processing of OCT images by presenting algorithms that automatically quantify epidermal thickness. …”
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AI-Driven Belt Failure Prediction and Prescriptive Maintenance with Motor Current Signature Analysis by João Paulo Costa, José Torres Farinha, Mateus Mendes, Jorge O. Estima

“…The incorporation of LSTM networks and swarm intelligence algorithms led to a significant improvement in predictive capabilities, allowing for the early detection of degradation patterns and timely intervention. …”
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Comparative Study and Real-World Validation of Vertical Load Estimation Techniques for Intelligent Tire Systems by Ti Wu, Xiaolong Zhang, Dong Wang, Weigong Zhang, Deng Pan, Liang Tao

“…Existing studies have mainly focused on modeling and bench experiments, overlooking a detailed comparative analysis of real sensor performance and validation under actual driving conditions. …”
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Enhancing Mobile App Recommendations With Crowdsourced Educational Data Using Machine Learning and Deep Learning by Naadiya Mirbahar, Kamlesh Kumar, Asif Ali Laghari

“…Mobile devices make it easier to gather educational data through crowdsourcing, which opens new possibilities for improving app recommendation algorithms. This paper provides valuable methodologies for scalable student recommendation and educational systems, highlighting DL’s advantages over CF in handling sparse, time-sensitive datasets. …”
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Novel Approaches for the Early Detection of Glaucoma Using Artificial Intelligence by Marco Zeppieri, Lorenzo Gardini, Carola Culiersi, Luigi Fontana, Mutali Musa, Fabiana D’Esposito, Pier Luigi Surico, Caterina Gagliano, Francesco Saverio Sorrentino

“…Results: Convolutional neural networks (CNNs) and other deep learning algorithms are among the AI models included in this paper that have been shown to have excellent sensitivity and specificity in identifying glaucomatous alterations in fundus photos, OCT scans, and visual field tests. …”
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