A narrative review of the use of PROMs and machine learning to impact value-based clinical decision-making by Michal Pruski, Simone Willis, Kathleen Withers

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Energy consumption reduction for an ultra-low-cost artificial pancreas using an event-trigger MPC strategy by Jhon E. Goez-Mora, Pablo S. Rivadeneira

“…This work aims to evaluate the performance of an impulsive Model Predictive Control (MPC) strategy with an event-triggered (ET) approach implemented in an artificial pancreas (AP) system to determine if insulin injection is necessary, avoiding the execution of the control algorithm and the use of hardware associated to that in each sampling period. …”
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SPINEX-anomaly: similarity-based predictions with explainable neighbors exploration for anomaly and outlier detection by M. Z. Naser, Ahmad Z. Naser

“…Abstract This paper presents a novel anomaly and outlier detection algorithm from the SPINEX (Similarity-based Predictions with Explainable Neighbors Exploration) family. …”
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Construction of a risk prediction model for postoperative deep vein thrombosis in colorectal cancer patients based on machine learning algorithms by Xin Liu, Xingming Shu, Yejiang Zhou, Yifan Jiang

“…Moreover, the SHAP method identified age and preoperative prealbumin as the primary determinants influencing ML model predictions. Finally, the study employed LIME for more precise prediction and interpretation of individual predictions.ConclusionThe machine learning algorithms effectively predicted postoperative lower limb deep vein thrombosis in colorectal cancer patients. …”
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Development and Internal Validation of Machine Learning Algorithms for Predicting Subsequent Contralateral Slipped Capital Femoral Epiphysis in Patients With Unilateral Slips by David P. VanEenenaam, Jr., BS, Carter Hall, BS, Daniel A. Maranho, MD, PhD, Christopher J. DeFrancesco, MD, Eduardo N. Novais, MD, Wudbhav N. Sankar, MD

“…Machine learning (ML) algorithms can be leveraged to identify complex, nonlinear patterns in data and allow for more accurate predictions on which patients may need a prophylactic pin. …”
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Predicting College Student Engagement in Physical Education Classes Using Machine Learning and Structural Equation Modeling by Liguo Zhang, Jiarui Gao, Liangyu Zhao, Zetan Liu, Anlin Guan

“…Nine machine learning algorithms were employed to develop interpretable predictive models, rank the importance of digital technology tools, and identify the optimal predictive model for student engagement. …”
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Physics-informed deep learning with Kalman filter mixture for traffic state prediction by Niharika Deshpande, Hyoshin (John) Park

“…We propose an innovative approach to modifying both prediction and correction steps of the Kalman filter (KF) algorithm by leveraging established spatiotemporal correlations. …”
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SGRiT: Non-Negative Matrix Factorization via Subspace Graph Regularization and Riemannian-Based Trust Region Algorithm by Mohsen Nokhodchian, Mohammad Hossein Moattar, Mehrdad Jalali

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A PSO weighted ensemble framework with SMOTE balancing for student dropout prediction in smart education systems by Achin Jain, Arun Kumar Dubey, Shakir Khan, Arvind Panwar, Mohammad Alkhatib, Abdulaziz M Alshahrani

“…Abstract Student dropout is a critical issue that affects not only educational institutions but also students’ mental well-being, career prospects, and long-term quality of life. …”
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Optimization of Electric Transformer Operation Through Load Estimation Based on the K-Means Algorithm by Pedro Torres-Bermeo, José Varela-Aldás, Kevin López-Eugenio, Nancy Velasco, Guillermo Palacios-Navarro

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Enhancing student success prediction in higher education with swarm optimized enhanced efficientNet attention mechanism. by Meshari Alazmi, Nasir Ayub

“…Advanced machine-learning approaches are being used to understand student performance variables as educational data grows. A big dataset from several Chinese institutions and high schools is used to develop a credible student performance prediction technique. …”
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Prediction of undernutrition and identification of its influencing predictors among under-five children in Bangladesh using explainable machine learning algorithms. by Md Merajul Islam, Nobab Md Shoukot Jahan Kibria, Sujit Kumar, Dulal Chandra Roy, Md Rezaul Karim

“…Thus, the objectives of this study are to develop an appropriate model for predicting the risk of undernutrition and identify its influencing predictors among under-five children in Bangladesh using explainable machine learning algorithms.…”
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Prediction of Insulator ESDD Based on Meteorological Feature Mining and AdaBoost-MEA-ELM Model by Yaoping WANG, Te LI, Kaihua JIANG, Wenhui LI, Qiang WU, Yu WANG

Subjects: “…esdd prediction…”
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Optimizing knee osteoarthritis severity prediction on MRI images using deep stacking ensemble technique by Punita Panwar, Sandeep Chaurasia, Jayesh Gangrade, Ashwani Bilandi, Dayananda Pruthviraja

“…In order to address the limitation of time and expedite the diagnostic process, deep learning algorithms have been implemented in the medical field. …”
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ALGORITHM FOR ASSESSING TIME AND COST RISKS AT ENTERPRISES OF THE MILITARY-INDUSTRIAL COMPLEX by N.D. Pechalin, A.G. Finogeev

“…The objective is to create models and an algorithm for predictive risk analysis when drawing up a calendar schedule for the implementation of project tasks to support decisionmaking by managers of defense industry enterprises. …”

Quantum resonant dimensionality reduction by Fan Yang, Furong Wang, Xusheng Xu, Pan Gao, Tao Xin, ShiJie Wei, Guilu Long

“…Here, we propose a quantum resonant dimensionality reduction (QRDR) algorithm based on the quantum resonant transition to reduce the dimension of input data and accelerate the quantum machine learning algorithms. …”
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A Special Points and Neural Network-Based Dynamic Multi-Objective Optimization Algorithm by Sanyi Li, Wenjie Hou, Peng Liu, Weichao Yue, Qian Wang

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Cybersecure XAI Algorithm for Generating Recommendations Based on Financial Fundamentals Using DeepSeek by Iván García-Magariño, Javier Bravo-Agapito, Raquel Lacuesta

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Development of psychological and educational aspects of interaction between medical workers and patients by T. V. Ryabova, A. A. Mutigullina

Subjects: “…learning algorithm…”
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Ensemble design for seasonal climate predictions: studying extreme Arctic sea ice lows with a rare event algorithm by J. Sauer, F. Massonnet, G. Zappa, F. Ragone

“…Here, we apply a rare event algorithm to ensemble simulations with the intermediate-complexity coupled climate model PlaSim-LSG to study extremes of pan-Arctic sea ice area reduction under pre-industrial greenhouse gas conditions. …”
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