Predictive value of the stone-free rate after percutaneous nephrolithotomy based on multiple machine learning models by Zhao Rong Liu, Zhao Rong Liu, Zhan Jiang Yu, Jie Zhou, Jian Biao Huang

“…In addition, the SHAP analysis identified the number of stones and the stone CT value as the most critical features influencing the model’s predictions, contributing significantly to its overall predictive performance.ConclusionThe prediction models developed based on three machine learning algorithms can accurately predict the stone-free rate after PCNL in patients with urinary tract stones. …”
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A High-Resolution Spectral Analysis Method Based on Fast Iterative Least Squares Constraints by Yanyan Ma, Haixia Kang, Weifeng Luo, Yunxiao Zhang, Lintao Luo

Subjects: “…thickness prediction…”
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Optimizing Heart-Kidney Interaction for Cancer Detection Through Physiological Process Simulation as a Decision Support System by Najmeh Sadat Jaddi, Salwani Abdullah, Zalinda Othman, Yazrina Yahya, Mohd Zakree Ahmad Nazri, Say Leng Goh, Fatemeh Alvankarian, Jafar Alvankarian

Subjects: “…Heart-kidney algorithm…”
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Bridging the Gap Between Machine Learning and Medicine: A Critical Evaluation of the Dworak Regression Grade in Rectal Cancer by Camille Raets, Chaimae El Aisati, Amir L. Rifi, Mark De Ridder, Koen Putman, Johan De Mey, Alexandra Sermeus, Kurt Barbe

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Enhanced clash detection in building information modeling: Leveraging modified extreme gradient boosting for predictive analytics by Ali Shehadeh, Odey Alshboul, Madhar M. Taamneh, Aiman Q. Jaradat, Ahmad H. Alomari

“…The result justifies the model's performance and identifies its potential to streamline predictive analytics in BIM concerning clash detection. …”
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Predictability of Lifetime Nonsuicidal Self-injury by Symptoms of Sleep Disorders Using a Neural Network Model by Shakiba Rezaei, Azita Chehri, Saeede Sadat Hosseini, Mokhtar Arefi, Hassan Amiri

“…Conclusion: The neural network algorithm can be effectively employed in predicting NSSI by several sleep disorders. …”
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Predicting chronic pain using wearable devices: a scoping review of sensor capabilities, data security, and standards compliance by Johannes C. Ayena, Johannes C. Ayena, Amina Bouayed, Amina Bouayed, Myriam Ben Arous, Myriam Ben Arous, Youssef Ouakrim, Youssef Ouakrim, Karim Loulou, Karim Loulou, Darine Ameyed, Isabelle Savard, Leila El Kamel, Neila Mezghani, Neila Mezghani

“…Data extraction focused on device types, sensor quality, compliance with health standards, and the predictive algorithms employed.ResultsWearable devices show promise in correlating physiological markers with CP, but few studies integrate predictive models. …”
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Preoperative prediction of recurrence risk factors in operable cervical cancer based on clinical-radiomics features by Xue Du, Xue Du, Chunbao Chen, Lu Yang, Yu Cui, Min Li

“…ObjectiveTo investigate the value of preoperative prediction of risk factors for recurrence of operable cervical cancer based on the radiomics features of biparametric magnetic resonance imaging (bp-MRI) combined with clinical features.MethodA retrospective collection of cervical cancer cases undergoing radical hysterectomy + pelvic and/or para-aortic lymph node dissection at the Affiliated Hospital of North Sichuan Medical College was conducted. …”
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A multivariate analysis of the early dropout using classical machine learning and local interpretable model-agnostic explanations by Thanh Hai Nguyen, Phuong Le, Tuyen Thanh Thi Nguyen, Anh Kim Su

“…Consequently, many institutions are focused on identifying key factors that contribute to dropout and implementing strategies to mitigate them. This study aims to predict student dropout rates using classical machine learning algorithms while analyzing the key factors influencing these outcomes in higher education. …”
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A multivariate analysis of the early dropout using classical machine learning and local interpretable model-agnostic explanations by Thanh Hai Nguyen, Phuong Le, Tuyen Thanh Thi Nguyen, Anh Kim Su

“…Consequently, many institutions are focused on identifying key factors that contribute to dropout and implementing strategies to mitigate them. This study aims to predict student dropout rates using classical machine learning algorithms while analyzing the key factors influencing these outcomes in higher education. …”
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Advancing Credit Rating Prediction: The Role of Machine Learning in Corporate Credit Rating Assessment by Nazário Augusto de Oliveira, Leonardo Fernando Cruz Basso

“…This study investigated the potential of machine-learning (ML) algorithms as a more precise and adaptable alternative for credit rating predictions. …”
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Optimized Model Predictive Control-Based Path Planning for Multiple Wheeled Mobile Robots in Uncertain Environments by Yang She, Chao Song, Zetian Sun, Bo Li

“…Addressing the path planning problem for multiple wheeled mobile robots (WMRs) in uncertain environments, this paper proposes a multi-WMR path planning algorithm based on the fusion of artificial potential field and model predictive control. …”
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Nonlinear Recurrent Neural Network Predictive Control for Energy Distribution of a Fuel Cell Powered Robot by Qihong Chen, Rong Long, Shuhai Quan, Liyan Zhang

“…Because the dynamic of the system is viewed as operating- state- dependent time varying local linear behavior in this frame, a linear constrained model predictive control algorithm is developed to optimize the power splitting between the fuel cell and ultracapacitor. …”
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Energy Management Strategy for Hybrid Electric Vehicles Based on Adaptive Equivalent Ratio-Model Predictive Control by Farah Mahdi Ali, Nizar Hadi Abbas

“…This paper develops an optimal energy management algorithm based on Model Predictive Control that can produce optimal control parameters for power distribution between the battery unit and generator. …”
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Machine Learning-Based Modelling and Predictive Maintenance of Turning Operation under Cooling/Lubrication for Manufacturing Systems by Gurpreet Singh, Jothi Prabha Appadurai, Varatharaju Perumal, K. Kavita, T. Ch Anil Kumar, DVSSSV Prasad, A. Azhagu Jaisudhan Pazhani, K. Umamaheswari

“…These three processes are developed to predict the machine learning force, cutting power, and cutting pressure by controlling primary factors (cutting speed, depth of cut, and feed rate). …”
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Assessing the predictive power of immune microenvironment-related genes and clinical immune-inflammatory parameters in breast cancer by Shangyi Lu, Shun Liang, Fucai Chen, Jianyuan Meng, Junwei Chen, Yi Lu, Gangjian Zhu

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Research on Feed Forward Adaptive-generalized Model Predictive Control for High-speed Train Automatic Operation by LUO Yuan, YI Jie, BAI Jinlei, ZHANG Zhengfang

“…Furthermore, a feed forward generalized prediction speed tracking control algorithm is designed based on the multi-object function, aiming to solve controller overshoot due to additional resistance changes and enhance control convergence rates. …”
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Improved Modulated Model Predictive Control: Reducing Total Harmonic Distortion, Computational Burden, and Parameter Sensitivity by Seyed Rasul Eftekhari, Ali Mosallanejad, Hamidreza Pairo, Jose Rodriguez

“…This paper presents an improved modulated model predictive control (M2PC) method, which is implemented on synchronous reluctance motor (SynRM) drives, significantly enhancing performance by streamlining the control algorithm. …”
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Evaluation of the effectiveness of an intervention strategy in a control simulation experiment through comparison with model predictive control by R. Nagai, Y. Bai, M. Ogura, M. Ogura, S. Kotsuki, S. Kotsuki, N. Wakamiya

“…This study evaluates CSE's efficacy against model predictive control (MPC), a well-established method in control engineering. …”
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Predictive modeling of Bifidobacterium animalis subsp. lactis Bb-12 growth in cow’s, goat’s and soy milk by Vedran Slačanac, Mirela Lučan, Jovica Hardi, Kristina Habschied, Vinko Krstanović, Goran Gagula

“…The aim of this study was to use a predictive model to analyse the growth of a probiotic strain Bifidobacterium animalis subsp. lactis Bb-12 in cow’s, goat’s and soy milk. …”
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