Development and Validation of a Machine Learning Model for Early Prediction of Delirium in Intensive Care Units Using Continuous Physiological Data: Retrospective Study by Chanmin Park, Changho Han, Su Kyeong Jang, Hyungjun Kim, Sora Kim, Byung Hee Kang, Kyoungwon Jung, Dukyong Yoon

“…ObjectiveWe aimed to create a novel machine learning model for delirium prediction in ICU patients using only continuous physiological data. …”
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An optimized feature selection using triangle mutation rule and restart strategy in enhanced slime mould algorithm by Ibrahim Musa Conteh, Gibril Njai, Abass Conteh, Qingguo Du

“…Then we combine the TRSMA with Support Vector Machines (SVM) and propose the TRSMA-SVM model to select the joint feature and classifier parameters. …”
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Artificial Intelligence Optimization for User Prediction and Efficient Energy Distribution in Electric Vehicle Smart Charging Systems by Siow Jat Shern, Md Tanjil Sarker, Mohammed Hussein Saleh Mohammed Haram, Gobbi Ramasamy, Siva Priya Thiagarajah, Fahmid Al Farid

“…The study leverages machine learning models such as Random Forest, Support Vector Regression (SVR), Gradient Boosting Regressor, XGBoost, LightGBM, and Long Short-Term Memory (LSTM) to forecast user demand and optimize energy allocation. …”
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Development of a mathematical model of an autonomous power supply source with a free piston motor on the basis of a synchronous electric returning machine with a permanent magnets by A. R. Safin, I. V. Ivshin, E. I. Gracheva, T. I. Petrov

“…Using a synchronous electric reciprocating machine with permanent magnets in power plants of a modular type makes it possible to rationally design an autonomous power supply source, to obtain the most optimal design. …”
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Gender classification performance optimization based on facial images using LBG-VQ and MB-LBP by Faruq Abdul Hakim, Tio Dharmawan, Muhamad Arief Hidayat

“…In conclusion, this study successfully formed an optimized gender classification model based on the FEI facial images dataset.…”
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Empirical analysis of control models for different converter topologies from a statistical perspective by Hole Shreyas Rajendra

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Prediction model for chemical explosion consequences via multimodal feature fusion by Yilin Wang, Beibei Wang, Yichen Zhang, Jiquan Zhang, Yijie Song, Shuang-Hua Yang

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Large language models to facilitate pregnancy prediction after in vitro fertilization by Ping Cao, Ganesh Acharya, Andres Salumets, Masoud Zamani Esteki

“…The results suggest that LLMs can facilitate data processing, optimize machine learning models in predicting IVF success rates, and provide data interpretation methods. …”
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Effective Identification of Variety and Origin of Chenpi Using Hyperspectral Imaging Assisted with Chemometric Models by Hangxiu Liu, Youyou Wang, Yiheng Wang, Jingyi Wang, Hanqing Hu, Xinyi Zhong, Qingjun Yuan, Jian Yang

“…Convolutional neural networks (CNNs) were developed and compared with conventional machine learning models, including partial least-squares discriminant analysis (PLS-DA), support vector machines (SVMs), and a multilayer perceptron (MLP). …”
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Risk prediction and effect evaluation of complicated appendicitis based on XGBoost modeling by Sunmeng Chen, Jianfu Xia, Beibei Xu, Yi Huang, Miaomiao Teng, Juyi Pan

“…Conclusion Predictive models based on the XGBoost algorithm have good performance in predicting the risk of acute appendicitis progressing to complicated appendicitis, which helps to optimize clinical decision making.…”
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Development of a Disease Model for Predicting Postoperative Delirium Using Combined Blood Biomarkers by Hengjun Wan, Huaju Tian, Cheng Wu, Yue Zhao, Daiying Zhang, Yujie Zheng, Yuan Li, Xiaoxia Duan

“…Patients were divided into the postoperative delirium (N = 100) and non‐postoperative delirium (N = 455) groups. Based on machine learning, linear and nine non‐linear models were developed and compared to select the optimal model. …”
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Comparison of 7 artificial intelligence models in predicting venous thromboembolism in COVID-19 patients by Indika Rajakaruna, Mohammad Hossein Amirhosseini, Mike Makris, Mike Laffan, Yang Li, Deepa J. Arachchillage

“…Additionally, it achieved the highest area under the curve score (0.983). Conclusion: The SVC model delivered the best overall performance outperforming similar studies that developed deep learning and machine-learning models for COVID-19.…”
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Optimizing DNA Sequence Classification via a Deep Learning Hybrid of LSTM and CNN Architecture by Elias Tabane, Ernest Mnkandla, Zenghui Wang

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Multi-strategy enhanced artificial rabbits optimization for prediction of grades in tourism service communication courses by Xiaodan Qu, Zhuyin Jia

“…Experimental results on the collected student performance dataset demonstrate that the KELM model optimized by MEARO surpasses other benchmark models across various metrics. …”
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University proceedings. Volga region. Technical sciences by V.V. Konovalov, M.V. Dontsova, A.N. Rasstegaev, V.Yu. Zaitsev

“…The purpose of the research is to develop a computer model for optimizing the loading of machines of the same classification group, but of different types, of the existing fleet of technological equipment of the enterprise. …”

Estimation the pH of CO2-saturated NaCl solutions using gene expression programming: Implications for CO2 sequestration by Mohammad Rasool Dehghani, Parirokh Ebrahimi, Moein Kafi, Hamed Nikravesh, Yousef Kazemzadeh

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Exploration and comparison of the effectiveness of swarm intelligence algorithm in early identification of cardiovascular disease by Tiantian Bai, Mengru Xu, Taotao Zhang, Xianjie Jia, Fuzhi Wang, Xiuling Jiang, Xing Wei

“…This study systematically evaluated the performance of each feature selection algorithm under different population sizes, specifically by comparing their average running time and objective function values to identify the optimal feature subset. Subsequently, the selected feature subsets were integrated into ten classification models, and a comprehensive weighted evaluation was performed based on the accuracy, precision, recall, F1 score, and AUC value of the model to determine the optimal model configuration. …”
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Research on Financial Stock Market Prediction Based on the Hidden Quantum Markov Model by Xingyao Song, Wenyu Chen, Junyi Lu

“…This quantum-enhanced model empowers investors to predict market regimes (bullish/bearish/range-bound) using real-time data, enabling dynamic portfolio adjustments, optimized risk controls, and data-driven allocation shifts.…”
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The modified theoretical model for debris flows predication with multiple rainfall characteristic parameters by Shengdong Cai, Zizhao Zhang, Xiaolong Yang, Qianli Lv, Xinyu Liu, Runsen Lai, Xikun Yu, Yang Hu

“…Subsequently, various machine learning methods were employed to determine the optimal impact weights of these rainfall characteristics. …”
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Predicting Dilution in Underground Mines with Stacking Artificial Intelligence Models and Genetic Algorithms by Jorge L. V. Mariz, Tertius S. G. Ferraz, Marinésio P. Lima, Ricardo M. A. Silva, Hyongdoo Jang

“…The models include support vector machines, neural networks, and tree-based approaches. …”
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