Development and Validation of Machine Learning Models for Outcome Prediction in Patients with Poor-Grade Aneurysmal Subarachnoid Hemorrhage Following Endovascular Treatment by Du S, Wu Y, Tao J, Shu L, Yan T, Xiao B, Lv S, Ye M, Gong Y, Zhu X, Hu P, Wu M

“…We further use Shapley Additive Explanations (SHAP) methods for the distribution of feature visualization based on the optimal models.Results: A total of 226 eligible patients with poor-grade aSAH undergoing EVT were enrolled, while 89 (39.4%) has a poor 12-month outcome. …”
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AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women by Li Ma, Li Ma, Ru Chen, Weigong Ge, Paul Rogers, Beverly Lyn-Cook, Huixiao Hong, Weida Tong, Ningning Wu, Wen Zou

“…In addition, BERTopic has the connection port for ChatGPT-4-Turbo or other large language models in its algorithm for automatic interpretation, while with LDA interpretation must be manually, and needs special procedures for data pre-processing and stop words exclusion. …”
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Research of Physical and Mechanical Properties of Self-Compacting Concrete Based on Polyfractional Binder by Meiram M. Begentayev, Daniyar A. Akhmetov, Rauan E. Lukpanov, Erzhan I. Kuldeyev, Zhanar O. Zhumadilova, Tolebi Myrzaliyev, Duman S. Dyussembinov, Aigerim K. Tolegenova

“…A software and calculation complex featuring a three-dimensional modeling algorithm, Drop and Roll, was used to select the optimal composition. …”
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High-Precision Indoor Visible Light Positioning Using Deep Neural Network Based on the Bayesian Regularization With Sparse Training Point by Haiqi Zhang, Jiahe Cui, Lihui Feng, Aiying Yang, Huichao Lv, Bo Lin, Heqing Huang

“…All of the aforementioned experimental results show that the algorithm and training data optimization we proposed provide a new solution for real-time and high-accuracy positioning with the neural network.…”
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Efficient Resource Allocation and UAV Deployment in STAR-RIS and UAV-Relay Assisted Public Safety Networks for Video Transmission by Naveed Khan, Ayaz Ahmad, Abdulmalik Alwarafy, Munam Ali Shah, Abderrahmane Lakas, Muhammad Moazam Azeem

“…This optimization is subject to several constraints. The formulated optimization problem is non-convex, posing a challenge in solving it. …”
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The potentials of vehicle-grid integration on peak shaving of a community considering random behavior of aggregated vehicles by Yalun Li, Kun Wang, Chaojie Xu, Yu Wu, Liguo Li, Yuejiu Zheng, Shichun Yang, Hewu Wang, Minggao Ouyang

“…Through analysis of the global optimization results, the comparison of disorderly charging with VGI under different scenarios is provided to illustrate the effectiveness of avoiding load uplift and reducing load peak-valley range. …”
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Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics by Xiao Li, Bo Wang, Xiaocong Li, Juan He, Yue Shi, Rui Wang, Dongwei Li, Ding Haitao, Ding Haitao

“…Machine learning algorithms were subsequently used to identify the optimal combination of diagnostic biomarkers. …”
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Opportunities, Challenges, and Future Directions for Generative Artificial Intelligence in Library Information Literacy Education: A Scoping Review by Fan YUAN, Jia LI

“…This methodological approach enabled a thorough exploration of current practices while identifying critical gaps in existing research. …”
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Predicting Index Trend Using Hybrid Neural Networks with a Focus on Multi-Scale Temporal Feature Extraction in the Tehran Stock Exchange by Mohammad Osoolian, Ali Nikmaram, Mahdi Karimi

“…Moreover, to further enhance the performance and resilience of the model, sophisticated feature engineering methodologies are implemented to optimize its overall functionality. ResultsThe results of the study reveal that while the hybrid neural network model, integrating CNN and LSTM components, demonstrates promising capabilities in predicting the TSE Composite Index, its accuracy falls short compared to competing models, particularly at weekly and monthly time scales. …”
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Evaluation of Neural, Systemic and Extracerebral Activations During Active Walking Tasks in Older Adults Using fNIRS by Meltem Izzetoglu, Roee Holtzer

“…Nevertheless, efforts to optimize extraction of fNIRS-derived brain signal measurements should continue taking advantage of technological advancement.…”
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Atrial fibrillation and chronic kidney disease: main clinical characteristics of patients in selected subjects of the Russian Federation by M. A. Druzhilov, T. Yu. Kuznetsova, O. Yu. Druzhilova, U. D. Arustamova, D. V. Gavrilov, A. V. Gusev

“…This emphasizes the need to optimize risk stratification, ACT and algorithms for the prevention of athero­thrombotic events, as well as the development of nephro­protective strategies to reduce the rate of progression of renal dys­function in this cohort of patients.…”
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Predictive Modeling of Acute Respiratory Distress Syndrome Using Machine Learning: Systematic Review and Meta-Analysis by Jinxi Yang, Siyao Zeng, Shanpeng Cui, Junbo Zheng, Hongliang Wang

“…Future research should standardize model development, optimize model performance, and explore how to better integrate predictive models into clinical practice to improve ARDS diagnosis and risk stratification. …”
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A Synergistic Approach to Colon Cancer Detection: Leveraging EfficientNet and NSGA-II for Enhanced Diagnostic Performance by Noushin Saba, Afia Zafar, Mohsin Suleman, Kainat Zafar, Shahneer Zafar, Adil Ali Saleem, Hafeez Ur Rehman Siddiqui, Muhammad Iqbal, Syed Sajid Ullah

“…We employed EfficientNet, a state-of-the-art convolutional neural network, to extract intricate features from histopathological images, alongside the Non-dominated Sorting Genetic Algorithm II for optimal feature selection. This hybrid approach significantly enhances diagnostic performance while reducing computational complexity. …”
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An enhanced substation equipment detection method based on distributed federated learning by Zhuyun Li, Qiutong Qin, Yingyi Yang, Xiaoming Mai, Yuya Ieiri, Osamu Yoshie

“…For FL, the Federated Adaptive (FedAdp) algorithm reduces communication rounds by 62% compared to Federated Averaging (FedAvg), maintaining near-centralized accuracy while preserving data locality. …”
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Hyperspectral imaging combined with residual-attention-net for spectral-spatial feature fusion in liver disease diagnosis by Yunze Li, Jingjing Wang, Miaoqing Zhao, Jinlin Deng, Chongxuan Tian, Qize Lv, Yifei Liu, Kun Ru, Wei Li

“…We incorporated band selection techniques, including the Norris derivative and the Successive Projections Algorithm (SPA), and optimized the data processing workflow. …”
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Capacity Estimation of Lithium-Ion Battery Systems in Fuel Cell Ships Based on Deep Learning Model by Xiangguo Yang, Jia Tang, Qijia Song, Yifan Liu, Lin Liu, Xingwei Zhou, Yuelin Chen, Telu Tang

“…A TCN-BiGRU model is then developed, with hyperparameters determined by the Kepler optimization algorithm (KOA). Cells from a battery pack under consistent conditions are used for training, while other cells in the same pack serve as the test set. …”
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Hot deformation physical mechanisms and a unified constitutive model of a solid solution Ti55511 alloy deformed in the two-phase region by Huijie Zhang, Y.C. Lin, Gang Su, Yongfu Xie, Wei Qiu, Ningfu Zeng, Song Zhang, Guicheng Wu

“…Finally, process parameters are optimized based on the model to achieve favorable microstructures.…”
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Real-Time Integration of Optical Coherence Tomography Thickness Map Overlays for Enhanced Visualization in Epiretinal Membrane Surgery: A Pilot Study by Ferhat Turgut, Keisuke Ueda, Amr Saad, Tahm Spitznagel, Luca von Felten, Takashi Matsumoto, Rui Santos, Marc D. de Smet, Zoltán Zsolt Nagy, Matthias D. Becker, Gábor Márk Somfai

“…By improving surgical precision while potentially reducing complications, this technique benefits both surgeons and patients. …”
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Prevention and Management of Spinal Cord Ischemia After Aortic Surgery: An Umbrella Review by Alexandros G. Brotis, Adamantios Kalogeras, Metaxia Bareka, Eleni Arnaoutoglou, Kostas Spanos, Miltiadis Matsagkas, Kostas N. Fountas

“…The prompt management of spinal cord complications is crucial to optimizing outcomes. No clear treatment algorithm has been universally adopted. …”
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Evaluating the impact of deep learning approaches on solar and photovoltaic power forecasting: A systematic review by Oussama Khouili, Mohamed Hanine, Mohamed Louzazni, Miguel Angel López Flores, Eduardo García Villena, Imran Ashraf

“…Accurate solar and photovoltaic (PV) power forecasting is essential for optimizing grid integration, managing energy storage, and maximizing the efficiency of solar power systems. …”
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