Additional lung – a rare malformation by S. A. Karavaeva, A. V. Podkamenev, T. V. Patrikeeva, M. M. Aleshugin, M. V. Golubeva, А. G. Li, R. A. Ti, D. A. Malekov, A. I. Tashchilkin, O. A. Murashova

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Development of Explainable Machine Learning Models to Identify Patients at Risk for 1-Year Mortality and New Distant Metastases Postendoprosthetic Reconstruction for Lower Extremit... by Jiawen Deng, BHSc, Myron Moskalyk, BHSc, MSc, Madhur Nayan, MD, PhD, Ahmed Aoude, MEng, MD, FRCSC, Michelle Ghert, MD, FRCSC, Sahir Bhatnagar, PhD, Anthony Bozzo, MSc, MD, FRCSC

“…LightGBM was identified as the best-performing algorithm for both outcomes. For 1-year mortality prediction without percent necrosis, LightGBM achieved an area under the receiver operating characteristic curve (AUC-ROC) of 0.78 (95% confidence interval [CI] 0.70-0.86) during cross-validation and 0.72 on internal validation. …”
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Exposing Face Manipulation Based on Generative Adversarial Network–Transformer and Fake Frequency Noise Traces by Qiaoyue Man, Young-Im Cho

“…In recent years, with the application of GANs and diffusion generative network algorithms, many highly realistic synthetic images are emerging, greatly increasing the potential for misuse, and deepfakes have become a serious social concern. …”
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Parameter estimation for networked SIR models with stochastic perturbations using JEKF: a study using COVID-19 daily data from Indian states by Prince Achankunju, Saroj Kumar Dash

“…This sophisticated estimation algorithm iteratively predicts and refines the state based on current estimates, combining model predictions with observed data to enhance accuracy, making it effective for estimating critical parameters in dynamic systems. …”
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Sparse long short-term memory for information fusion in wireless sensor networks by Yangfan Zhou, Mingchuan Zhang, Ping Xie, Junlong Zhu, Ruijuan Zheng, Qingtao Wu

“…Furthermore, the prediction accuracy of the sparse long short-term memory algorithm is almost the same as the other comparison algorithms.…”
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Soft Sensor Modeling of Key Effluent Parameters in Wastewater Treatment Process Based on SAE-NN by Yousuf Babiker M. Osman, Wei Li

“…A soft sensor model is studied to predict the BOD5 in a wastewater treatment plant to evaluate the proposed approach. …”
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How Re-Infections and Newborns Can Impact Visible and Hidden Epidemic Dynamics? by Igor Nesteruk

“…With the use of effective algorithms for parameter identification, the proposed approach can ensure effective predictions of visible and hidden numbers of cases and infectious and removed patients.…”
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Exploring the Role of Artificial Intelligence in Dental Implantology: A Scholarly Review by Abdulrahman Ahmed Aseri

“…AI-based technologies, such as machine learning algorithms, neural networks, and computer vision, are being increasingly utilized to interpret diagnostic imaging, predict implant outcomes, and customize treatment protocols tailored to individual patient needs. …”
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Employee loyalty evaluation using machine learning in technology-based small and medium-sized enterprises by Yong Shi, Yuan Wang, Hongkun zuo

“…Through several machine learning models and algorithms to predict employee loyalty, the feasibility of machine learning to predict employee loyalty is proved, and the evaluation of talent in TSMEs is supported by decision analysis. …”
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Potential geographical distribution of Carob tree (Ceratonia siliqua L., Leguminosae) in Morocco under climate change by Jalal Kassout, Soufian Chakkour, Abdeltif El Ouahrani, Younes Hmimsa, Salama El Fatehi, Yanzheng Yan, Rachid Hadria, Mohammed Ater

“…Our hypothesis suggests a reduction in suitable habitats for the carob tree under climate change scenarios. …”
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Eecs-fl: energy-efficient client selection for federated learning in AIoT by Yiyang Zhang, Yiming Luo, Tao Yang, Xiaofeng Wu, Bo Hu

“…Experimental results show that incorporating WPT leads to a reduction in unit energy consumption by over 24.54%; while, the proposed algorithm achieves a reduction of over 15.31% compared to random selection. …”
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Interperiod coherent integration of the received signal with a variable repetition period of the probing signal by S. R. Heister, P. G. Semashko

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Assessing Similarity Between Datasets Using Vector Representations by А. А. Usatoff, A. M. Nedzved, Guo Jiran

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Using Machine Learning for Recognition of Alzheimer’s Disease Based on Transcription Information by U. A. Vishniakou, Chu Yue Yu

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An Advanced Hybrid Forecasting System for Wind Speed Point Forecasting and Interval Forecasting by Haipeng Zhang, Hua Luo

“…Therefore, in this paper, we developed a prediction system integrating an advanced data preprocessing strategy, a novel optimization model, and multiple prediction algorithms. …”
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Are Electromyography Data a Fingerprint for Patients with Cerebral Palsy (CP)? by Mehrdad Davoudi, Firooz Salami, Robert Reisig, Dimitrios A. Patikas, Nicholas A. Beckmann, Katharina S. Gather, Sebastian I. Wolf

“…Regarding EMG, a significant reduction was only observed in the ND of the rectus femoris (<i>p</i>-value < 0.001) and soleus (<i>p</i>-value = 0.006). …”
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THE USE OF INTERACTIVE STUDYING METHODS IN TEACHING OPERATIVE SURGERY AND TOPOGRAPHIC ANATOMY by V.M. Fedorak

“…However, on the ground of current laws it’s totally impossible to obtain cadaveric material and organs of dead people, and strict requirements of Bioethics Commission on the use of animals in education led to a strong reduction of lessons performed on animals. …”
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Time Series Data Augmentation for Energy Consumption Data Based on Improved TimeGAN by Peihao Tang, Zhen Li, Xuanlin Wang, Xueping Liu, Peng Mou

“…After data augmentation, the prediction model exhibits significant reductions in RMSE and MAE along with an increase in the R² value. …”
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Dynamic Bayesian Network Model for Overhead Power Lines Affected by Hurricanes by Kehkashan Fatima, Hussain Shareef

“…To characterize the stochastic properties of HIF, Monte Carlo simulation (MCS) is employed in conjunction with fragility curves (FC) and the scenario reduction (SCENRED) algorithm. The proposed DBN model evaluates the probability of asset failure and compares the results using stochastic Monte Carlo simulation based on the fragility curve scenario reduction algorithm (FC-MCS-SCENRED) model. …”
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Occupant-Centric Visual Comfort Assessment and Optimization of Passive Solar Façade Shading Systems through View-Based Analysis of Daylight Glare Probability, View Content, and Spa... by Martin Ivanov, Jun Sato

“…The proposed framework employs an adaptive optimization algorithm that iteratively generates and refines shading device configurations, effectively balancing glare reduction, external visibility, and visual complexity. …”
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