Derivation and external validation of a risk prediction algorithm to estimate future risk of cardiovascular death among patients with type 2 diabetes and incident diabetic nephropathy: prospective cohort study by Bin Zhao, Jin Shang, Xiaoxue Zhang

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Classical and Quantum Algorithms for Characters of the Symmetric Group by Sergey Bravyi, David Gosset, Vojtech Havlicek, Louis Schatzki

“…Here we describe a matrix product state (MPS) algorithm for characters of S_{n}. The algorithm computes an MPS encoding all irreducible characters of a given permutation. …”
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Maintenance Time Prediction for Predictive Maintenance of Ship Engines by Seunghun Lim, Jungmo Oh, Jinkyu Park

“…However, due to the nature of ship operation, data collection is difficult, and most studies focus on fault detection, hindering the application of predictive maintenance to ships. In this study, we developed a maintenance time prediction algorithm using the revision generator engine condition criterion (RGCCV) value and the cylinder exhaust gas temperature, as developed in a previous study for marine generator engines. …”
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Comparison of fast regression algorithms in large datasets by Sengul Cangur, Handan Ankarali

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Hybrid statistical-algorithmic approach using the frog algorithm to optimize blast patterns for reducing blast vibrations by Abbas Khajouei Sirjani, Farhang Sereshki, Mohammad Ataei, Manoj Khandelwal, Hojatollah Mohammadi Anayi, Seyed Mohammad Mehdi Mousavi Nasab, Mohammad Amiri Hosseini

“…This study introduces an innovative approach to predict and mitigate blast-induced vibrations by optimizing blast patterns. …”
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Multipath Estimation of Navigation Signals Based on Extended Kalman Filter–Genetic Algorithm Particle Filter Algorithm by Jie Li, Xiyan Sun, Yuanfa Ji, Jingjing Li, Long Li

“…This method utilizes the EKF to calculate the mean and covariance of samples using the latest observation information, providing a more reasonable proposal density for particle filtering and enhancing the accuracy of state prediction. Simultaneously, by introducing the crossover and mutation mechanisms of the adaptive genetic algorithm, particles are continuously evolved during the resampling process, preventing them from falling into local extrema. …”
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Research on parameter selection and optimization of C4.5 algorithm based on algorithm applicability knowledge base by Yiyan Zhang, Yi Xin, Qin Li

“…Abstract Given that the decision tree C4.5 algorithm has outstanding performance in prediction accuracy on medical datasets and is highly interpretable, this paper carries out an optimization study on the selection of hyperparameters of the algorithm in order to achieve fast and accurate optimization of the algorithm model. …”
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A Method for Predicting Coal-Mine Methane Outburst Volumes and Detecting Anomalies Based on a Fusion Model of Second-Order Decomposition and ETO-TSMixer by Qiangyu Zheng, Cunmiao Li, Bo Yang, Zhenguo Yan, Zhixin Qin

“…The ability to predict the volume of methane outbursts in coal mines is critical for the prevention of methane outburst accidents and the assurance of coal-mine safety. …”
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Jordan–Schur Algorithms for Computing the Matrix Exponential by Petko H. Petkov

“…Instead of the Schur form, these algorithms use the Jordan–Schur form of A. The Jordan–Schur form is found by less computation and it is determined more reliable than the reduction to Jordan form since it is obtained using only unitary similarity transformations. …”
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Accurate and robust prediction of Amyloid-β brain deposition from plasma biomarkers and clinical information using machine learning by Jiayuan Xu, Andrew J. Doig, Sofia Michopoulou, Sofia Michopoulou, Petroula Proitsi, Petroula Proitsi, Fumie Costen, The Alzheimer's disease neuroimaging initiative

“…This study aims to develop and validate machine learning algorithms for accurately predicting brain Aβ positivity using plasma biomarkers, genetic information, and clinical data as a cost-effective alternative to PET imaging.MethodsWe analyzed 1,043 patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset and validated our models on 127 patients from the Center for Neurodegeneration and Translational Neuroscience (CNTN) dataset. …”
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A Dynamic Neural Network Optimization Model for Heavy Metal Content Prediction in Farmland Soil by Kun Cao, Cong Zhang, Liangliang Li, Shuaifeng Li

Subjects: “…soil heavy metal content prediction…”
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A Comprehensive Review and Benchmarking of Fairness-Aware Variants of Machine Learning Models by George Raftopoulos, Nikos Fazakis, Gregory Davrazos, Sotiris Kotsiantis

“…We analyze these adaptations in terms of their methodological adjustments, impact on algorithmic bias and ability to maintain predictive performance comparable to the original models.…”
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Safety Status Prediction Model of Transmission Tower Based on Improved Coati Optimization-Based Support Vector Machine by Xinxi Gong, Yaozhong Zhu, Yanhai Wang, Enyang Li, Yuhao Zhang, Zilong Zhang

“…Subsequently, we employ the improved coati optimization algorithm (ICOA) to refine the penalty parameters and kernel function of the support vector machine (SVM), thereby developing the safety state prediction model for the transmission tower. …”
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Interpretable machine learning approaches for predicting prostate cancer by using multiple heavy metal exposures based on the data from NHANES 2003–2018 by Zu-Ming You, Yuan-Sheng Li, Fan-Shuo Meng, Rui-Xiang Zhang, Chen-Xi Xie, Zhijiang Liang, Ji-Yuan Zhou

“…The synergistic effect analysis further identified blood Pb, urinary Sb, and urinary Cs as the major contributing factors. The predictive model established in this study can provide valuable strategies for the prevention and the control of PCA.…”
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Compressive strength prediction of fly ash/slag-based geopolymer concrete using EBA-optimised chemistry-informed interpretable deep learning model by Yang Yu, Iman Munadhil Abbas Al-Damad, Stephen Foster, Ali Akbar Nezhad, Ailar Hajimohammadi

“…The CNN architecture includes two convolution layers, global max-pooling, and two fully connected layers, with 11 input variables and a single output for CS prediction. To optimise model accuracy, the enhanced bat algorithm (EBA) is designed for metaparameter tuning. …”
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Hybrid CNN-Transformer-WOA model with XGBoost-SHAP feature selection for arrhythmia risk prediction in acute myocardial infarction patients by Li Li, Wenjun Ren, Yuying Lei, Lixia Xu, Xiaohui Ning

Subjects: “…Arrhythmia prediction…”
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Proposed Long Short-Term Memory Model Utilizing Multiple Strands for Enhanced Forecasting and Classification of Sensory Measurements by Sotirios Kontogiannis, George Kokkonis, Christos Pikridas

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DeepInvesting: Stock market predictions with a sequence-oriented BiLSTM stacked model – A dataset case study of AMZN by Ashkan Safari, Mohammad Ali Badamchizadeh

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Benchmarking network algorithms for contextualizing genes of interest. by Abby Hill, Scott Gleim, Florian Kiefer, Frederic Sigoillot, Joseph Loureiro, Jeremy Jenkins, Melody K Morris

“…In this work, we evaluate seventeen previously published algorithms based on characteristics of their output and their performance in three tasks: cross validation, prediction of drug targets, and behavior with random input. …”
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Development of AI in the Caribbean: algorithms, challenges and recommendations by Amir Mohammed, Sheikh Ahad Ahmad

“…Central to AI systems are algorithms that discover patterns and make predictions, eliminating the need for meticulous programming. …”
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