Development and Validation of an Interpretable Machine Learning Model for Prediction of the Risk of Clinically Ineffective Reperfusion in Patients Following Thrombectomy for Ischem... by Hu X, Qi D, Li S, Ye S, Chen Y, Cao W, Du M, Zheng T, Li P, Fang Y

“…Our CIR risk prediction platform enables early intervention and personalized treatment. …”
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MODEL PREDICTIVE CONTROL FOR PHOTOVOLTAIC STATION MAXIMUM POWER POINT TRACKING SYSTEM by I. Elzein, Yu. N. Petrenko

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Machine learning techniques for predictive modelling in geotechnical engineering: a succinct review by Shrikant M. Harle, Rajan L. Wankhade

“…Key areas of focus include the prediction of foundation settlement, where various ML algorithms—such as regression models, hybrid approaches, and numerical analysis techniques—are emphasized for their contributions to real-time monitoring and risk management. …”
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Smart agriculture using IoT for automated irrigation, water and energy efficiency by Subir Gupta, Subrata Chowdhury, Ramya Govindaraj, Kassian T.T. Amesho, Sumarlin Shangdiar, Timoteus Kadhila, Sioni Iikela

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Prediction of Airline Ticket Price Using Machine Learning Method by Hüseyin Korkmaz

“…This paper aims to predict ticket prices based on airline flight data using ML algorithms and to compare the performance of ML algorithms. …”
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Enhancing Cloud Security: A Multi-Factor Authentication and Adaptive Cryptography Approach Using Machine Learning Techniques by K. Sasikumar, Sivakumar Nagarajan

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Evaluating the Performance and Potential Bias of Predictive Models for Detection of Transthyretin Cardiac Amyloidosis by Jonathan Hourmozdi, MD, MSAI, MA, Nicholas Easton, MSAI, Simon Benigeri, MSAI, James D. Thomas, MD, Akhil Narang, MD, David Ouyang, MD, Grant Duffy, BS, Ross Upton, PhD, Will Hawkes, PhD, Ashley Akerman, PhD, Ike Okwuosa, MD, Adrienne Kline, MD, PhD, Abel N. Kho, MD, Yuan Luo, PhD, Sanjiv J. Shah, MD, Faraz S. Ahmad, MD, MS

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Machine learning-based prediction of short- and long-term mortality for shared decision-making in older hip fracture patients: the Dutch Hip Fracture Audit algorithms in 74,396 cases by Hidde Dijkstra, Cathleen S Parsons, Hanne-Eva VAN Bremen, Hanna C Willems, Anne A H De Hond, Barbara C van Munster, Job N Doornberg, Jacobien H F Oosterhoff

“…Conclusion: We developed and validated ML algorithms, including logistic regression, for mortality prediction in older hip fracture patients with adequate performance. …”
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Interpretable machine learning for predicting isolated basal septal hypertrophy. by Lei Gao, Boyan Tian, Qiqi Jia, Xingyu He, Guannan Zhao, Yueheng Wang

“…However, no predictive models for BSH have been developed using machine learning algorithms.…”
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A New Self-Tuning Nonlinear Model Predictive Controller for Autonomous Vehicles by Yasin Abdolahi, Sajad Yousefi, Jafar Tavoosi

“…The model predictive controller (MPC) is one of the efficient approaches by which the speed and direction of the near future of an automobile could be predicted and controlled. …”
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Systematic review railway infrastructure monitoring: From classic techniques to predictive maintenance by Giovanni Bianchi, Chiara Fanelli, Francesco Freddi, Felice Giuliani, Aldo La Placa

“…Recent Artificial Intelligence (AI) algorithms, which enable the use of digital tools such as Data-Driven models that can automatically adapt system operation, make decisions and suggest strategies based on collected data, form the basis of modern Predictive Maintenance (PdM). …”
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Predictive diagnostics of computer systems logs using natural language processing techniques by Vladislav A. Kiriachek, Soltan I. Salpagarov

“…This study aims to develop and validate a method for predictive diagnostics and anomaly detection in computer system logs, using the Vertica database as a case study. …”
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Assessment of Machine Learning Methods for Concrete Compressive Strength Prediction by Oluwafemi Omotayo, Chinwuba Arum, Catherine Ikumapayi

“…The study considered a wide range of literature data and examined the efficiency of boosted algorithms in predicting the strength of ordinary Portland cement concrete. …”
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Predictive Control for Earthquake Response Mitigation of Buildings Using Semiactive Fluid Dampers by F. Oliveira, P. Morais, A. Suleman

“…A predictive control strategy in conjunction with semiactive control algorithms is proposed for damping control of base-isolated structures employing semiactive fluid dampers when subjected to earthquake loads. …”
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The Artificial Intelligence and the dispute for different ways in its predictive use in the criminal process by Rodrigo Régnier Chemim Guimarães

“…Given the delicate cooperation that must exist between experts in criminal procedure and knowledge engineers in the selection and construction of the algorithms that will teach the machine for the preparation of the predictive research, which one would be appropriate? …”
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Machine learning in predicting firm performance: a systematic review by Yaseen Hezam, Hoa Luong, Lilian Anthonysamy

“…It aims to assess the effectiveness of various ML methods and algorithms used in recent research, focusing on the prediction of firm performance across multiple dimensions. …”
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An Ensemble Learning-Based Predictive Parameterization Approach for Permanent Magnet Synchronous Machines by Sema Nur Ipek, Nur Bekiroglu, Murat Taskiran

“…An averaging voting ensemble model is developed by integrating the two highest-performing algorithms, LRNN and TRF, leveraging the strengths of both algorithms. …”
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A Decreasing Horizon Model Predictive Control for Landing Reusable Launch Vehicles by Guillermo Zaragoza Prous, Enric Grustan-Gutierrez, Leonard Felicetti

“…A novel approach to model predictive control (MPC) with a decreasing horizon is analysed for guiding and controlling reusable launch vehicles (RLVs) during powered descent phases. …”
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Population-level predictive variation in machine learning diagnosis of symptomatic bacterial vaginosis by Diandra P. Ojo, Cameron Celeste, Dion Ming, Ruogu Fang, Ivana K. Parker

“…To determine the ability of ML models to perform equitably, this study evaluates the performance of ML algorithms in predicting symptomatic BV across different ethnic groups using 16S rRNA sequencing data. …”
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A network-based approach for predicting missing pathway interactions. by Saket Navlakha, Anthony Gitter, Ziv Bar-Joseph

“…Unlike existing algorithms for predicting general protein interactions, by focusing on proteins involved in specific responses our approach homes-in on pathway-consistent interactions. …”
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