Clinical Prediction Models Based on Traditional Methods and Machine Learning for Predicting First Stroke: Status and Prospects by ZHANG Zijiao, DING Shunjing, ZHAO Di, LIANG Jun, LEI Jianbo

“…In recent years, advancements in big data and artificial intelligence technologies have opened new avenues for stroke risk prediction. This article reviews the current research status of traditional methods and machine learning models in predicting first-ever stroke risk and outlines future development trends from three perspectives: First, emphasis should be placed on technological innovation by incorporating advanced algorithms such as deep learning and large models to further enhance the accuracy of predictive models. …”
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Integrating proximal geophysical sensing and machine learning for digital soil mapping: Spatial prediction and model evaluation using a small dataset by Danilo César de Mello, Gustavo Vieira Veloso, Murilo Ferre de Mello, Marcos Guedes de Lana, Isabelle de Angeli Oliveira, Fellipe Alcantara de Oliveira Mello, Rafael Gomes Siqueira, Lucas Carvalho Gomes, Elpídio Inácio Fernandes-Filho, Carlos Ernesto Gonçalves Reynaud Schaefer, Márcio Rocha Francelino, Emilson Pereira Leite, Tiago Osório Ferreira, José Alexandre Melo Demattê

“…However, studies focusing the spatial prediction of geophysical data remain limited. In this research, we aimed to model and predict the spatial distribution of soil geophysical properties using parent material and terrain attributes with machine learning algorithms. …”
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Enhancing Manufacturing Precision: Leveraging Motor Currents Data of Computer Numerical Control Machines for Geometrical Accuracy Prediction Through Machine Learning by Lucijano Berus, Jernej Hernavs, David Potocnik, Kristijan Sket, Mirko Ficko

“…Different machine learning algorithms, such as Random Forest (RF), k-nearest neighbors (k-NN), and Decision Trees (DT), were used for predictive modeling. …”
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Adaptable Reduced-Complexity Approach Based on State Vector Machine for Identification of Criminal Activists on Social Media by Imran Shafi, Sadia Din, Zahid Hussain, Imran Ashraf, Gyu Sang Choi

“…This study proposes simplified yet adaptable framework that uses a novel features extraction algorithm for extracting features from the textual part of social media contents. …”
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A SHAP algorithm-based prediction of the interlaminar shear strength degradation of G/BFRP bars embedded in concrete exposed to marine environment by Xuan Zhao, Pei-Fu Zhang, Qi Zhao, Daxu Zhang, Yiliyaer Tuerxunmaimaiti, Heng Cao

“…To address this issue, a dataset collected from published literature was compiled and SHAP algorithm-based method was employed to predict the ILSS retention (ILSSR). …”
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Prediction-Based Distributed State Estimation Control for IoT-Enabled Train Positioning Systems by L. Ponnarasi, P. B. Pankajavalli, Y. Lim, R. Sakthivel, Sultan Alfarhood, Mejdl Safran

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Remaining useful life prediction of a small sample of aero-engine based on an improved gray Markov model by Dong-hai Li, Ji-liang Tu, Hui Liu, Nai-zhi Liao

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Crop Type Classification by DESIS Hyperspectral Imagery and Machine Learning Algorithms by Nizom Farmonov, Khilola Amankulova, Jozsef Szatmari, Alireza Sharifi, Dariush Abbasi-Moghadam, Seyed Mahdi Mirhoseini Nejad, Laszlo Mucsi

“…However, precise and continuous spectral signatures, important for large-area crop growth monitoring and early prediction of yield production with cutting-edge algorithms, can be only provided via hyperspectral imaging. …”
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Predicting the Magnitude of Earthquakes Using Grammatical Evolution by Constantina Kopitsa, Ioannis G. Tsoulos, Vasileios Charilogis

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A python approach for prediction of physicochemical properties of anti-arrhythmia drugs using topological descriptors by Huiling Qin, Mudassar Rehman, Muhammad Farhan Hanif, Muhammad Yousaf Bhatti, Muhammad Kamran Siddiqui, Mohamed Abubakar Fiidow

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Half-hourly electricity price prediction model with explainable-decomposition hybrid deep learning approach by Sujan Ghimire, Ravinesh C. Deo, Konstantin Hopf, Hangyue Liu, David Casillas-Pérez, Andreas Helwig, Salvin S. Prasad, Jorge Pérez-Aracil, Prabal Datta Barua, Sancho Salcedo-Sanz

“…Input features are identified using the Partial Autocorrelation Function , and models are optimized using the Optuna algorithm. The final prediction combines the trend, seasonal, and residual components’ predictions. …”
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An improved deep learning model for soybean future price prediction with hybrid data preprocessing strategy by Dingya CHEN, Hui LIU, Yanfei LI, Zhu DUAN

Subjects: “…soybean future price prediction…”
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Classification of imbalanced travel mode choice dataset with SMOTE and prediction using interpretable machine learning by Mujahid Ali

“…Therefore, the current study used the Synthetic Minority Oversampling Technique (SMOTE) to balance the TMC dataset and used several ML algorithms such as random forest (RF), decision tree (DT), Extreme Gradient Boosting (XGBoost), K-nearest Neighbors (KNN), and logistic regression for the prediction of TMC. …”
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Algorithm for selecting predictors and prognosis of atrial fibrillation in patients with coronary artery disease after coronary artery bypass grafting by B. I. Geltser, K. I. Shakhgeldyan, V. Yu. Rublev, B. O. Shcheglov, E. A. Kokarev

“…These values in best model based on multivariate LR were lower (0,75; 0,7; 0,68 and 0,7, respectively).Conclusion. The developed algorithm for selecting predictors made it possible to verify significant predictive ranges and weight coefficients characterizing their influence on PAF development. …”
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Prospects of Predicting the Polar Motion Based on the Results of the Second Earth Orientation Parameters Prediction Comparison Campaign by Tomasz Kur, Justyna Śliwińska‐Bronowicz, Malgorzata Wińska, Henryk Dobslaw, Jolanta Nastula, Aleksander Partyka, Santiago Belda, Christian Bizouard, Dale Boggs, Sara Bruni, Lue Chen, Mike Chin, Sujata Dhar, Robert Dill, PengShuo Duan, Jose M. Ferrandiz, Junyang Gou, Richard Gross, Sonia Guessoum, Songtao Han, Robert Heinkelmann, ChengLi Huang, Christopher Irrgang, Jacek Kudrys, Jia Li, Marcin Ligas, Lintao Liu, Weitao Lu, Volker Mayer, Wei Miao, Maciej Michalczak, Sadegh Modiri, Michiel Otten, Todd Ratcliff, Shrishail Raut, Jan Saynisch‐Wagner, Matthias Schartner, Erik Schoenemann, Harald Schuh, M. Kiani Shahvandi, Benedikt Soja, Xiaoqing Su, Daniela Thaller, Maik Thomas, Guocheng Wang, Yuanwei Wu, CanCan Xu, Xueqing Xu, Xinyu Yang, Xin Zhao, Zhijin Zhou

“…Abstract Growing interest in Earth Orientation Parameters (EOP) resulted in various approaches to the EOP prediction algorithms, as well as in the exploitation of distinct input data, including the observed EOP values from various operational data centers and modeled effective angular momentum functions. …”
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A Modified Kalman Filter Based on Radial Basis Function Neural Networks for the Improvement of Numerical Weather Prediction Models by Athanasios Donas, George Galanis, Ioannis Pytharoulis, Ioannis Th. Famelis

“…This study introduces a novel enhancement to the Kalman filter algorithm by integrating it with Radial Basis Function neural networks to improve numerical weather prediction models. …”
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Progress and perspectives in data assimilation algorithms for remote sensing and crop growth model by Jianxi Huang, Jianjian Song, Hai Huang, Wen Zhuo, Quandi Niu, Shangrong Wu, Han Ma, Shunlin Liang

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Predicting the chemical equilibrium point of reacting components in gaseous mixtures through a novel Hierarchical Manta-Ray Foraging Optimization Algorithm by Oguz Emrah Turgut, Hadi Genceli, Mustafa Asker, Mustafa Turhan Çoban, Mohammad Akrami

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Kerf geometry prediction and optimization in laser cutting of basalt fiber reinforced polymer composites using decision tree and coati optimization algorithm by Ammar H. Elsheikh, Ninshu Ma, Fadl A. Essa, Mahmoud Khedr, Ahmed Mohamed Mahmoud Ibrahim

“…This study introduces a Coati Optimization Algorithm (COA) integrated with a Decision Tree (DT) algorithm to predict and optimize kerf geometry in Basalt Fiber Reinforced Polymer (BFRP) composites during laser cutting. …”
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Development and validation of a spontaneous preterm birth risk prediction algorithm based on maternal bioinformatics: A single-center retrospective study by Yu Chen, Xinyan Shi, Zhiyi Wang, Lin Zhang

“…In terms of predicting the risk of preterm birth, the XGBoost algorithm demonstrated the most outstanding performance, with an AUCROC of 0.89 (95% CI: 0.88–0.90). …”
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