Implementation of the healthy heart tool- an algorithm with potential cardiometabolic health benefits in persons with severe mental illness by Elisabeth Haug Lund-Stenvold, Petter A. Ringen, Ole A. Andreassen, Torfinn L. Gaarden, Cecilie B. Hartberg, Erik Johnsen, Silje Myklatun, Kåre Osnes, Kjetil Sørensen, Arne Vaaler, Serena Tonstad, John A. Engh, Anne Høye

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A Scoring Algorithm for the Early Prediction of Academic Risk in STEM Courses by Vanja Čotić Poturić, Sanja Čandrlić, Ivan Dražić

Subjects: “…educational data mining…”
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Geoinformation monitoring of the educational risk in educational institutions of higher education by Aleksandr N. Kolesenkov, Dmitry S. Zhuravlyov

“…The effect, received by a person and society from mastering the basic professional educational programs is problematic to quantify, which leads to the emergence of a risk that characterizes the quality of management decision-making procedures for implementing the educational process in higher education institutions in terms of the level of achievement of the set criteria and indicators.The aim of the work is the development of technology for monitoring of the educational risk based on the geoinformation approach and methods of data mining. …”
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Comprehensive review of dimensionality reduction algorithms: challenges, limitations, and innovative solutions by Aasim Ayaz Wani

“…This review introduces a unified classification—linear, nonlinear, hybrid, and ensemble approaches—and assesses them against eight core challenges: dimensionality selection, overfitting, instability, noise sensitivity, bias, scalability, privacy risks, and ethical compliance. We outline solutions such as intrinsic dimensionality estimation, robust neighborhood graphs, fairness-aware embeddings, scalable algorithms, and automated tuning. …”
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Development of a justification process for selecting alternative risk reduction measures by Pavlo Saik, Vitalii Tsopa, Olena Yavorska, Serhii Cheberiachko, Mariia Brezitska, Andrii Yavorskyi, Vasyl Lozynskyi, Vasyl Lozynskyi

“…An eleven-step risk management process was designed to determine alternative preventive measures, characterized by feedback loops that enable the selection of optimal risk reduction strategies.ResultsThis study presents algorithms for solving three types of decision-making problems regarding the selection of combinations of preventive measures from a defined set of alternatives. …”
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Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk by Mohamed Chaouch, Omama M. Al-Hamed

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Focus on Disaster Risk Reduction by ResNet-CDMV Model After Natural Disasters by Zhaojia Tang, Yu Han

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Predicting Bank Loan Risks Using Machine Learning Algorithms by Maan Alsaleem, Safwan Hasoon

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Auditing Flood Vulnerability Geo-Intelligence Workflow for Biases by Brian K. Masinde, Caroline M. Gevaert, Michael H. Nagenborg, Marc J. C. van den Homberg, Jacopo Margutti, Inez Gortzak, Jaap A. Zevenbergen

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Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

“…This study investigates and predicts the likelihood of operational risk occurrence in the banking industry using machine learning algorithms. …”
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A dimension reduction assisted credit scoring method for big data with categorical features by Tatjana Miljkovic, Pei Wang

“…We argue that current studies related to the development of credit scoring models have largely ignored recent developments in statistical methods for sufficient dimension reduction. To contribute to the field of financial innovation, this study proposes a Dimension Reduction Assisted Credit Scoring (DRA-CS) method via distance covariance-based sufficient dimension reduction (DCOV-SDR) in Majorization-Minimization (MM) algorithm. …”
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Postpartum depression risk prediction using explainable machine learning algorithms by Xudong Huang, Lifeng Zhang, Chenyang Zhang, Jing Li, Chenyang Li

“…The key predictive factors included weight gain during pregnancy, relationship with the mother-in-law, sleep quality, marital relationship, planned pregnancy, fetal sex preference, pregnancy-related anxiety, pelvic-floor muscle endurance, cervix status, attendance at prenatal education classes, and postpartum care satisfaction.ConclusionThe XGBoost model demonstrated optimal performance at predicting PPD and can aid healthcare professionals to identify high-risk individuals. …”
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Development of a Quantitative Assessment Algorithm for Operational Risks in Mining Engineering by Marina Nevskaya, Anna Shabalova, Liubov Nikolaichuk, Natalya Kirsanova

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A new algorithm to assess the risk of malignancy in premenopausal patients with pelvic mass by M. S. Katsyuba, R. Sh. Khasanov, T. I. Madzhidov, G. Z. Muratova, G. A. Usmanova, A. F. Akhmetzyanova, A. Rakhimbekova, V. V. Terentyeva, G. R. Fakhrutdinova

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Algorithm of echocardiography in pregnant women by S. G. Gorokhova, T. E. Morozova, A. A. Arakelyants, E. A. Barabanova, E. G. Dyakonova

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Seismic Vulnerability Assessment of Reinforced Concrete Educational Buildings Using Machine Learning Algorithm by Tapan Kumar, Mohammad Al Amin Siddique, Raquib Ahsan

“…The main objective of this paper is to assess the vulnerability of reinforced concrete (RC) educational buildings in Dhaka city to seismic activity by utilizing machine learning (ML) algorithms. …”
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Nonlinear Volatility Risk Prediction Algorithm of Financial Data Based on Improved Deep Learning by Wangsong Xie

“…To increase the prediction accuracy of financial data, a new nonlinear volatility risk prediction algorithm is proposed based on the improved deep learning algorithm. …”
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Enhancing cybersecurity via attribute reduction with deep learning model for false data injection attack recognition by Faheed A.F. Alrslani, Manal Abdullah Alohali, Mohammed Aljebreen, Hamed Alqahtani, Asma Alshuhail, Menwa Alshammeri, Wafa Sulaiman Almukadi

“…The ARDL-FDIAR technique uses Z-score normalization to scale the input data. The attribute reduction process gets invoked using the modified Lemrus optimization algorithm (MLOA) to choose optimal feature sets. …”
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Predictive analytics in gamified education: A hybrid model for identifying at-risk students by Devanshu Sawarkar, Latika Pinjarkar, Pratham Agrawal, Devansh Motghare

“…This research proposes a hybrid predictive model designed to identify at-risk students within a gamified education environment accurately. …”
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Multi-objective Optimal Scheduling of Water-Carbon in Cascade Reservoirs during Impoundment for Carbon Emission Reduction by ZHOU Yan-lai, NING Zhi-hao, HE Jun-tao

“…[Methods] Given that current studies on cascade reservoir impoundment scheduling have not yet incorporated carbon reduction objectives, this study proposed a multi-objective water-carbon scheduling model for cascade reservoirs during impoundment period based on the carbon emission factor method.An early storage strategy for cascade reservoirs was developed,and three objectives—minimizing flood control risk,maximizing power generation,and minimizing greenhouse gas emissions—were established.The Non-dominated Sorting Genetic Algorithm Ⅱ (NSGA-Ⅱ) was employed to derive optimal scheduling schemes for the impoundment period.…”
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