A logistic regression-based model for predicting heart failure mortality by Krstić Marija, Krstić Lazar

Subjects: “…predictive model…”
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A Fractal Model for Predicting the Relative Permeability of Rough-Walled Fractures by Zuyang Ye, Wang Luo, Shibing Huang, Yuting Chen, Aiping Cheng

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The PLANS model predicts recurrent strokes in patients with minor ischemic strokes by Zhi-Xin Huang, Haike Lu, Yi Lu, Yingyi Dai, Jianguo Lin, Zhenguo Liu

“…Abstract Minor ischemic stroke (MIS) patients face significant risks of recurrent strokes, necessitating reliable predictive tools. This single-center retrospective study developed and validated a novel model for predicting 1-year stroke recurrence in MIS patients, defined as those with National Institutes of Health Stroke Scale scores < 4 within seven days of symptom onset. …”
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Prediction of success of slings in female stress incontinence, statistical and AI modeling by Bassem S. Wadie, Ahmed Abdelrasheed, Mohammed Taha, Ahmed Abdelrahman, Bassam Mohamed, Alaa Saber, Ahmed Badawi

“…In this study, we tested a statistical regression model and an AI model for the prediction of the outcome of mid-urethral sling. …”
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Double-Weighted Bayesian Model Combination for Metabolomics Data Description and Prediction by Jacopo Troisi, Martina Lombardi, Alessio Trotta, Vera Abenante, Andrea Ingenito, Nicole Palmieri, Sean M. Richards, Steven J. K. Symes, Pierpaolo Cavallo

“…Background/Objectives: This study presents a novel double-weighted Bayesian Ensemble Machine Learning (DW-EML) model aimed at improving the classification and prediction of metabolomics data. …”
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MODEL FOR MONITORING AND PRODUCTION PREDICTING IN SUNFLOWER CROP BASED ON SATELLITE IMAGES by Daniel DICU, Radu BERTICI, Mihai HERBEI, Florin SALA

“…The study provided useful information on the temporal variability of sunflower crop and production prediction in relation to agricultural technology and is the basis of agricultural crop management models.…”
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Model of metabolism and gene expression predicts proteome allocation in Pseudomonas putida by Juan D. Tibocha-Bonilla, Vishant Gandhi, Chloe Lieng, Oriane Moyne, Rodrigo Santibáñez-Palominos, Karsten Zengler

“…Compared to a metabolic-only model, iPpu1676-ME significantly expands on gene expression, macromolecular assembly, and cofactor utilization, enabling accurate growth predictions without additional constraints. …”
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Prediction of the monthly river water level by using ensemble decomposition modeling by Chaitanya Baliram Pande, Lariyah Mohd Sidek, Bijay Halder, Okan Mert Katipoğlu, Jitendra Rajput, Fahad Alshehri, Rabin Chakrabortty, Subodh Chandra Pal, Norlida Mohd Dom, Miklas Scholz

“…Abstract The decomposition, artificial intelligence (AI) and machine learning (ML) modeling have been important role in hydrological and river basin related prediction and forecasting to help the flood management and sustainable water resources development. …”
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Effective workflow from multimodal MRI data to model-based prediction by Kyesam Jung, Kevin J. Wischnewski, Simon B. Eickhoff, Oleksandr V. Popovych

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Construction of disability risk prediction model for the elderly based on machine learning by Jing Chen, Yifei Ren, Jie Ding, Qingqing Hu, Jiajia Xu, Jun Luo, Zhaowen Wu, Ting Chu

Subjects: “…Prediction model…”
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Prediction of Gas Solubility in Ionic Liquids Using the Cosmo-Sac Model by Jaschik Manfred, Piech Daniel, Warmuzinski Krzysztof, Jaschik Jolanta

“…The predictions of the COSMOSAC model for N2 and O2 in ILs differ from the pertinent experimental data. …”
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Landslide Displacement Prediction Model Based on Time Series and CNN-GRU by FU Zhentao, LI Limin, WANG Lianxia, REN Ruibin, CUI Chengtao, FENG Qingqing

“…Landslide displacement prediction is an important basis for early landslide warning.This paper proposes a prediction model of landslide moving states based on time series and convolutional gated recurrent unit (CNN-GRU) to deal with the shortcomings of previous prediction models.Firstly,after employing wavelet analysis to determine the displacement of the trend term,the exponential smoothing method is adopted to decompose the cumulative displacement to obtain two displacement types of the trend term and the periodic term,and the trend term is fitted by a five-order polynomial.Then,the autocorrelation function is utilized to test the periodic displacement characteristics,and the gray correlation method is applied to determine the correlation degree between each factor and the periodic term.Meanwhile,the periodic term and the influencing factor are input into the CNN-GRU model for prediction,and finally the predicted cumulative displacement value is obtained by superposition.By taking the Baishui River landslide in the Three Gorges Reservoir area as an example,this paper selects the data from January 2004 to December 2012 for study,and the average absolute error percentage of the final prediction results is only 0.525%,with RMSE of 9.614 and R² of 0.993.Experimental results show that CNN-GRU has higher prediction accuracy.…”
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Presenting a prediction model for HELLP syndrome through data mining by Boshra Farajollahi, Mohammadjavad Sayadi, Mostafa Langarizadeh, Ladan Ajori

Subjects: “…Prediction model…”
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Simulation and prediction of rural population changes using agent-based modeling by Shanshan Huang, Yao Huang, Shitai Bao, Jianfang Wang, Siying Chen

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An Hourly Prediction Model of Relativistic Electrons Based on Empirical Mode Decomposition by Yedong Qian, Jianwei Yang, Hua Zhang, Chao Shen, Yewen Wu

“…After a long period, such an electron flux effect could cause satellites to be unable to function properly or to fail completely. Unlike previous prediction models of relativistic electrons focusing mainly on forecasting the daily value, we have developed an hourly prediction model to learn more detailed changes. …”
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Prediction of ship maneuvering motion in regular wave with gray-box modelling by Yang HAN, Lizhu HAO, Chao SHI, Ziying PAN, Jiang LU, Min GU

“…ObjectivesAiming at the requirements of the real-time and accurate prediction of ship maneuvering motion, this paper investigates the prediction of ship maneuvering motion in regular waves using gray-box modelling to improve the accuracy. …”
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Machine Learning-Based Mortality Risk Prediction Model in Patients with Sepsis by Zhang Y, Li C, Ji Y, Wei B, Guo S, Mei X, Wang J

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An Integrated Cellular Automata Model Improves the Accuracy of Secondary Fragmentation Prediction by René Gómez, Camila San Martin, Raúl Castro

“…This work describes the application of a new model to improve the accuracy of the prediction of fine material in block caving mining by coupling a stress model and a fragmentation model, integrating the shear strain effect. …”
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Prediction of Continuous Rain Disaster in Henan Province Based on Markov Model by Xiaoxiao Zhu, Shuhua Zhang, Bingjun Li

“…Taking the maize in Henan Province as an example, the Markov model is used to predict the occurrence of continuous rain in the middle growth and late growth stages (flowering and filling stages) of 13 cities in Henan Province. …”
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Grain Yield Prediction Based on the Improved Unbiased Grey Markov Model by Wu Yuan, Zhou Rui, Yu Bao, Huang Xiang, Li Bo

“…In order to improve the accuracy of grain yield prediction, this paper proposes a grain yield prediction method with improved unbiased grey Markov model. …”
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