Multicenter Development and Prospective Validation of eCARTv5: A Gradient-Boosted Machine-Learning Early Warning Score by Matthew M. Churpek, MD, MPH, PhD, ATSF, Kyle A. Carey, MPH, Ashley Snyder, MPH, Christopher J Winslow, MD, Emily Gilbert, MD, Nirav S Shah, MD, MPH, Brian W. Patterson, MD, MPH, Majid Afshar, MD, MSCR, Alan Weiss, MD, MBA, Devendra N. Amin, MD, Deborah J. Rhodes, MD, Dana P. Edelson, MD, MS

“…All adult patients admitted to the inpatient medical-surgical wards and at 21 hospitals from three health systems for retrospective (2009–2023) and prospective (2023–2024) external validation. PREDICTION MODEL:. Predictor variables (demographics, vital signs, documentation, and laboratory values) were used in a gradient-boosted trees algorithm to predict ICU transfer or death in the next 24 hours. …”
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A Novel Crowdsourcing-Assisted 5G Wireless Signal Ranging Technique in MEC Architecture by Rui Lu, Lei Shi, Yinlong Liu, Zhongkai Dang

“…Experimental results demonstrate a mean positioning error of 5 m, with 95% of devices achieving errors within 10 m, as well as building and floor prediction error rates of 0.5% and 1%, respectively. …”
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Machine Learning-Based Classification and Statistical Analysis of Liver Cancer: A Comprehensive Study of Model Performance and Clinical Significance by Pratyush Kumar MAHARANA, Tapan Kumar BEHERA, Pradeep Kumar NAIK

“…Conclusion: After performing the complete process, we conclude that the extra tree classifier out of 17 models is the most suitable machine learning algorithm for liver cancer prediction. …”
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Securing and optimizing optical transmission in quantum wells using OAM and advanced modulation techniques by Muhammad Ahmad, Zhiping Wang, Ming Fang, Zhixiang Huang, Guoda Xie

“…The Quantum Well Structure with Injection Locking Synchronization (QWS-ILCS) algorithm is proposed to improve the security of the transmission system. …”
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Real-Time Posture Correction of Squat Exercise: A Deep Learning Approach for Performance Analysis and Error Correction by Prashant Rao, C. S. Asha, P. Raghavendra Rao

“…To address these limitations, we propose a method that utilizes squat videos captured by a stereo camera. The MediaPipe algorithm extracts and tracks keypoints from video frames. …”
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Mechanistic role of miR-375 in regulating PDPK1 to promote progression of small bowel neuroendocrine tumors: a silico analysis by Tao Ren, Lu Zhou, Zhenlong Li, Mingmei Pan, Xueqiong Han

“…Drug targeting prediction and immune environment evaluation were identified. …”
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Energy saving and low carbon oriented renovation framework for educational buildings with Tianjin University case study by Xinge Du, Xiang Liu, Feng Gao, Zhihua Zhou

“…This study proposes a data-driven workflow that combines a genetic algorithm with a Bayesian optimization-based XGBoost model to optimize the retrofit design of educational buildings. …”
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Development of intelligent controller for high performance electric drives with hybrid CSA and RERNN technique by J. Prabhakaran, P. Thirumoorthi, M. Mathankumar, S. P. Mangaiyarkarasi

“…This research proposes a hybrid approach combining Circle Search Algorithm (CSA) and Recalling-Enhanced Recurrent Neural Network (RERNN), termed CSA-RERNN, for intelligent controller-fed electric drives. …”
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Improvement of physics-based and data-driven model simulations based on multi-source soil moisture datasets by Xiao Liang, Haiting Gu, Yue-Ping Xu, Lu Wang, Yuxue Guo, Li Liu

“…The physics-based Distributed-Hydrological-Soil-Vegetable Model (DHSVM), coupled with the multi-objective genetic algorithm ε-NSGA-II, and data-driven Informer model, are chosen and applied to the study area. …”
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Analysis of approaches to identification of trend in the structure of the time series by U. S. Mokhnatkina, D. V. Parfenov, D. A. Petrusevich

“…A combination of polynomial model for trend description and ARIMA for seasonally description and combination of ACD algorithm for trend and ETS for seasonal model obtained good forecasts in case of seasonal time series, while Fourier time series as a trend model also achieved close quality of prediction.Conclusions. …”
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Flood Detection and Susceptibility Mapping Using Sentinel-1 Time Series, Alternating Decision Trees, and Bag-ADTree Models by Ayub Mohammadi, Khalil Valizadeh Kamran, Sadra Karimzadeh, Himan Shahabi, Nadhir Al-Ansari

“…Based on AUC, success and prediction rates were 0.736 and 0.786 for bag-ADTree algorithm, in order, while these proportions were 0.714 and 0.784 for ADTree. …”
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Integrative omics analysis reveals the genetic basis of fatty acid composition in Brassica napus seeds by Yuting Zhang, Yunhao Liu, Zhanxiang Zong, Liang Guo, Wenhao Shen, Hu Zhao

“…To elucidate the genetic underpinnings governing fatty acid composition, we then employ a combination of GWAS, TWAS, and dynamic transcriptomic analysis during seed development, along with the POCKET algorithm. We predict six candidate genes that are associated with fatty acid composition. …”
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Rock blasting evaluation - image recognition method based on deep learning by Haibao YI, Aixiang Wu, Xiliang Zhang

“…In order to efficiently evaluate the quality of rock blasting in mines, this paper developed a blasting effect image analysis and calculation model and recognition algorithm based on the established machine learning database, and carried out recognition and analysis work on the half-hole rate and rock blasting fragmentation of pre-splitting blasting. …”
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Automatic identification and characteristics analysis of crack tips in rocks with prefabricated defects based on deep learning methods. by Mingtao Gao, Minhui Li, Lu Chen, Zihao Guo, Chengyang Guo, Liping Li, Changsen Bu

“…Especially in the rock specimen analysis of prefabricated multi-angle cracks, image quality and algorithm adaptability have emerged as the critical bottlenecks restricting the identification accuracy. …”
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Robust Adaptive Multiple Backtracking VBKF for In-Motion Alignment of Low-Cost SINS/GNSS by Weiwei Lyu, Yingli Wang, Shuanggen Jin, Haocai Huang, Xiaojuan Tian, Jinling Wang

“…Furthermore, the modified variational Bayesian Kalman filter (VBKF) that accurately adjusts the measurement noise covariance matrix is proposed, and the Expectation–Maximization (EM) algorithm is employed to refine the prior parameter of the predicted error covariance matrix. …”
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Development of a New Correlation Model for Heat Transfer in Solar Air Heater with Corrugated Absorber Plates Using Swarm Optimization by Abdulkadir Kocer, Uğur Ercan, Zeki Yetgin, Filiz Karaomerlioglu

“…As the main contribution, two different model equations, namely M1 and M2, for the correlation model of the solar heat transfer were proposed to predict the Nusselt number, where M2 is an original model and M1 is newly established with the fine-tuned coefficients. …”
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Investigating lightweight and interpretable machine learning models for efficient and explainable stress detection by Debasish Ghose, Ayan Chatterjee, Indika A. M. Balapuwaduge, Yuan Lin, Soumya P. Dash

“…Furthermore, our study has incorporated local interpretable model-agnostic explanations to provide comprehensive insights into the predictions made by the k-NN-based architecture.…”
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HIDS-RPL: A Hybrid Deep Learning-Based Intrusion Detection System for RPL in Internet of Medical Things Network by Abdelwahed Berguiga, Ahlem Harchay, Ayman Massaoudi

“…The suggested model, designated HIDS-RPL, results from the hybridization of the Convolutional Neural Network (CNN) for feature extraction and the Long Short Term Memory neural network (LSTM), typically employed for sequence data prediction. We evaluate the proposed algorithm to detect intrusions using the benchmark CIC-DDoS2019 dataset. …”
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MICROCIRCULATORY DISORDERS IN PATIENTS WITH ACUTE CORONARY SYNDROME by Sergey S. Krutitsky, Georgiy P. Plotnikov, Irina N. Sizova, Damir M. Galimzyanov, Dmitriy L. Shukevich, Evgeniy V. Grigoriev

“…Conclusions: Microcirculation parameters can be included in the diagnostic algorithm for ACS in patients with low cardiac output in order to predict cardiogenic shock and multiple organ failure. …”
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Crashworthiness and optimization for foam-filled multi-layer composite lattice structures by Jiye Chen, Wangwang He, Hai Fang, Yong Zhuang, Zhixiong Zhang, Yufeng Zhao

“…Additionally, the equivalent compressive modulus and compressive strength of the FMCLSs were predicted using a rule of mixtures.…”
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