Inflammation‐Derived and Clinical Indicator‐Based Predictive Model for Ischemic Stroke Recovery by Jiao Luo, You Cai, Peng Xiao, Changchun Cao, Meiling Huang, Xiaohua Zhang, Jie Guo, Yongyang Huo, Qiaoyan Tang, Liuyang Zhao, Jiabang Liu, Yaqi Ma, Anqun Yang, Mingchao Zhou, Yulong Wang

“…This study aimed to develop a predictive model, combining inflammation‐derived markers and clinical indicators, for distinguishing functional outcomes in patients with subacute ischemic stroke. …”
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Validation of sleep-based actigraphy machine learning models for prediction of preterm birth by Benjamin C. Warner, Peinan Zhao, Erik D. Herzog, Antonina I. Frolova, Sarah K. England, Chenyang Lu

“…We evaluate motion actigraphy data collected from a cohort of participants undergoing pregnancy, and train several machine learning models based on aggregate features engineered from this data. …”
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Machine learning for predicting distant metastasis in nasopharyngeal carcinoma patients by Hong Sun, Jijie Zhu, Ling Li, Xiu Xin, Jingchao Yan, Taomin Huang

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Developing a nomogram for risk prediction of the low T3 syndrome by Xiao-Li Feng, Hui-Min Chen, Liu-Juan Yin, Jin Chen, Li-Liang Chen

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Modeling, Small-Signal Stability Analyzing and Implementing of an Inverter-Based Distributed Generation with Feed-forwarded Model Predictive Controller by abdolhossein saleh

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ENHANCING DISEASE DETECTION PREDICTION ACCURACY OF GRAPE LEAVES USING VGG16 MODEL AND INCEPTION V3 MODEL by Deepshikha Yadav, Archana Balyan, Suman Mann, Aayush Ranga

“…Our comparative analysis not only delves into the models' predictive capabilities but also considers computational efficiency and resource requirements, providing valuable insights for agricultural practitioners and researchers engaged in precision farming and disease management. …”
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Evaluation and Prediction of Comprehensive Efficiency of Wind Power System in China Based on Two-Stage EBM Model and FNN Model by Fang-Rong Ren, Hui-Lin Liu, Xiao-Yan Liu

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Model Predictive Control with Optimal Modelling for Pneumatic Artificial Muscle in Rehabilitation Robotics: Confirmation of Validity Though Preliminary Testing by Dexter Felix Brown, Sheng Quan Xie

“…This paper presents a model predictive controller (MPC) based on dynamic models generated using the Particle Swarm Optimisation method for accurate motion control of a pneumatic artificial muscle (PAM) for application in rehabilitation robotics. …”
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Soil Moisture Content Prediction Using Gradient Boosting Regressor (GBR) Model: Soil-Specific Modeling with Five Depths by Tarek Alahmad, Miklós Neményi, Anikó Nyéki

“…These results highlight the necessity for soil-specific modeling to enhance SMC prediction accuracy, optimize irrigation systems, and support water resources management approaches aligning with SDG6 objectives.…”
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A Multi‐Model Ensemble of Baseline and Process‐Based Models Improves the Predictive Skill of Near‐Term Lake Forecasts by Freya Olsson, Tadhg N. Moore, Cayelan C. Carey, Adrienne Breef‐Pilz, R. Quinn Thomas

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On Predictive Modeling for the Al2O3 Data Using a New Statistical Model and Machine Learning Approach by Mahmoud El-Morshedy, Zahra Almaspoor, Gadde Srinivasa Rao, Muhammad Ilyas, Afrah Al-Bossly

“…In this article, we focused on predictive modeling for real data by means of a new statistical model and applying different machine learning algorithms. …”
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Developing clinical prognostic models to predict graft survival after renal transplantation: comparison of statistical and machine learning models by Getahun Mulugeta, Temesgen Zewotir, Awoke Seyoum Tegegne, Mahteme Bekele Muleta, Leja Hamza Juhar

“…This study aimed to develop prognostic models for predicting renal graft survival and compare the performance of statistical and machine learning models. …”
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Prediction of air quality perception in aircraft cabin based on psychophysical model and artificial neural network (ANN)-based model by Yihui Yin, Lei Zhao, Ruoyu You, Jingjing Pei, Hanyu Li, Junzhou He, Yuexia Sun, Xudong Yang, Qingyan Chen

“…Limited by the two basic assumptions that VOC interaction was non-existent and that the odor intensity was only related to VOC, the accuracy of OI calculated by the existing model was about 0.4. In order to improve the accuracy of evaluation, a new data-driven model for human perception (CAQ and OI) prediction based on a knowledge-based BP neural network was proposed, and its prediction accuracy (R2: 0.81–0.87) and generalization (R2: 0.76–0.93) were verified. …”
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Vocational High School (SMK) Students Accounting Competence Prediction Model by Using Astin I-E-O Model by Defi Sri Harwati, Heri Yanto

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Workforce predictive risk modelling: development of a model to identify general practices at risk of a supply−demand imbalance by Gary A Abel, John L Campbell, Sarah Gerard Dean, Chris Salisbury, Emily Fletcher, Mayam Gomez-Cano, Navonil Mustafee, Andi Smart, Rupa Chilvers, Suzanne H Richards, F Warren

“…Objective This study aimed to develop a risk prediction model identifying general practices at risk of workforce supply–demand imbalance.Design This is a secondary analysis of routine data on general practice workforce, patient experience and registered populations (2012 to 2016), combined with a census of general practitioners’ (GPs’) career intentions (2016).Setting/Participants A hybrid approach was used to develop a model to predict workforce supply–demand imbalance based on practice factors using historical data (2012–2016) on all general practices in England (with over 1000 registered patients n=6398). …”
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Aerodynamic Prediction and Design Optimization Using Multi-Fidelity Deep Neural Network by Bingchen Du, Ennan Shen, Jiangpeng Wu, Tongqing Guo, Zhiliang Lu, Di Zhou

“…The results of the prediction accuracy of the aerodynamic coefficients of airfoils show that the less HF data used, the more advantages can be achieved by the MFDNN models than the single-fidelity models. …”
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Exploring spatial machine learning techniques for improving land surface temperature prediction by Arunab K.S., Mathew A.

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Novel Conformable Fractional Order Unbiased Kernel Regularized Nonhomogeneous Grey Model and Its Applications in Energy Prediction by Wenkang Gong, Qiguang An

“…Experimental results show that the CFUKRNGM model achieves superior prediction accuracy and greater generalization performance compared to both the KRNGM and traditional grey models.…”
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MILLING FORCE MODELING BASED ON EQUIVALENT TURNING FORCE AND OBLIQUE CUTTING FORCE MODEL (MT) by WU MingZhou, ZHANG GuangPeng, LIU MoHan, GOU JianFeng, ZHANG Peng

Subjects: “…Equivalent model…”
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Advancing seasonal prediction of tropical cyclone activity with a hybrid AI-physics climate model by Gan Zhang, Megha Rao, Janni Yuval, Ming Zhao

Subjects: “…climate prediction…”
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