Is cardiovascular risk profiling from UK Biobank retinal images using explicit deep learning estimates of traditional risk factors equivalent to actual risk measurements? A prospec... by Kohji Nishida, Ryo Kawasaki, Yiming Qian, Liangzhi Li, Yuta Nakashima, Hajime Nagahara

“…In MACE prediction, our model outperformed the traditional score-based models, with 8.2% higher AUC than Systematic COronary Risk Evaluation (SCORE), 3.5% for SCORE 2 and 7.1% for the Framingham Risk Score (with p value<0.05 for all three comparisons).Conclusions Our algorithm estimates the 5-year risk of MACE based on retinal images, while explicitly presenting which risk factors should be checked and intervened. …”
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A Study on the Susceptibility of Wildfire Disasters in Wuzhou City Based on Interpretability Model by Lei Zou, Hongjuan Shao, Yintao Liu, Chao Ren, Qinyi Chen, Haoming Bai, Zhengzhong Huang, Yao Gu

“…The Extreme Gradient Boosting (XGBoost) algorithm was adopted to construct the prediction model, aiming to provide precise wildfire susceptibility assessment. …”
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Vibration, current, torque, RPM dataset for multiple fault conditions in industrial-scale electric motors under randomized speed and load variationsMendeley DataMendeley DataMendel... by Wonho Jung, Junho Kim, Kangmin Jang, Sung-Hyun Yun, Daeguen Lim, Minje Jin, Yong-Hwa Park

“…Unlike existing public datasets that often assume constant speed or isolated fault types, this dataset uniquely incorporates multi-fault, multi-severity conditions under randomized speed/load variations, filling critical gaps in real-world applicability for robust fault diagnosis algorithms. The dataset enables robust evaluation of machine learning models and signal processing algorithms for fault detection, condition monitoring, and predictive maintenance in rotating machinery. …”
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Pemodelan Sistem Monitoring Kualitas Udara Pintar Berbasis Internet of Things dengan Pendekatan Machine Learning by Eddy Prasetyo Nugroho, Ani Anisyah, Deva Shofa Al Fathin, Muhammad Nur Yasin Amadudin, Muhammad Satria Ramadhani, Yosafat

“…The combination of the real-time sensor and the LSTM algorithm resulted in an air quality prediction accuracy rate of 88%. …”
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Dynamic programming for home appliance scheduling with renewable energy integration by Iqra Rafiq, Anzar Mahmood, Ubaid Ahmed, Imran Aziz, Zafar Ali Khan

“…This study proposes an energy cost minimization model, which is solved using a single Knapsack algorithm combined with dynamic programming (DP). The Knapsack problem is used to schedule appliances and ensure that users and producers receive the maximum benefits in terms of cost minimization and peak-to-average ratio (PAR) reduction. …”
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Anoikis in hepatocellular carcinoma: genetic alterations and immune microenvironment insights from single-cell and computational analysis by Bing Zhou, Jialing Zhang, Mingfeng Guo

“…The prognostic model, developed using 101 algorithms, demonstrated the highest performance. High-risk patients showed poor prognosis, and the ROC curve analysis showed high accuracy for model predictions. …”
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Machine learning based calculation of refractive index of polyethylene glycol polymer by Walid Abdelfattah, Munthar Kadhim Abosaoda, Hardik Doshi, H.S. Shreenidhi, Manoranjan Parhi, Devendra Singh, Prabhjot Singh, Bilakshan Purohit, Kamal Kant Joshi, Ahmad Abumalek

“…This study develops advanced machine learning algorithms to accurately predict the refractive index of polyethylene glycol (PEG) polymers using temperature and molecular weight as key input variables. …”
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Quality of life and physical working capacity in pulmonary sarcoidosis by A. L. Gudim, L. B. Postnikova, V. A. Kostrov, A. A. Mironov, N. I. Kubysheva

“…In patients with low QOL, CPET can be used to determine the PWC and mechanisms of its reduction. The presented diagnostic algorithm will optimize the choice of therapy for patients with sarcoidosis.…”
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A multi‐objective feature optimization strategy for developing high‐entropy alloys with optimal strength and ductility by Yan Zhang, Shewei Xin, Wei Zhou, Xiao Wang, Yangyang Xu, Yanjing Su

“…Results show that the optimized feature subsets reduce prediction errors by 20% for strength and 11% for ductility. …”
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Advanced control parameter optimization in DC motors and liquid level systems by Serdar Ekinci, Davut Izci, Mohammad H. Almomani, Kashif Saleem, Raed Abu Zitar, Aseel Smerat, Vaclav Snasel, Absalom E. Ezugwu, Laith Abualigah

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Exploration of the clinicopathological and prognostic significance of BRCA1 in gastric cancer by Hongrong Zhang, Qi Xu, Hongxing Kan, Yinfeng Yang, Yunquan Cai

“…To explore potential biomarkers for GC, GC patient transcriptome data were subjected to a comprehensive approach involving machine learning, binary nomogram prediction model construction, the topological algorithm of CytoHubba, and Kaplan–Meier and Mendelian randomization (MR) analyses. …”
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Quantitative Detection of Quartz Sandstone SiO2 Grade Using Polarized Infrared Absorption Spectroscopy with Convolutional Neural Network Model by Banglong Pan, Hongwei Cheng, Shuhua Du, Hanming Yu, Shaoru Feng, Yi Tang, Juan Du, Huaming Xie

“…Then, generalized regression neural network (GRNN), partial least squares regression (PLSR), and convolutional neural network (CNN) were employed to establish a hyperspectral prediction model of SiO2 grade. The results show that the quantitative model by the PCA-CNN algorithm has the better prediction precision for the reciprocal logarithm data, with a coefficient of determination (R2), root mean square error (RMSE), and ratio of performance to interquartile range (RPIQ) of 0.907, 0.023, and 5.11, respectively. …”
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A Cascade of Encoder–Decoder with Atrous Convolution and Ensemble Deep Convolutional Neural Networks for Tuberculosis Detection by Noppadol Maneerat, Athasart Narkthewan, Kazuhiko Hamamoto

“…The ensemble classifier was designed to predict the presence of TB by fusing DCNNs from the winning combination via weighted averaging. …”
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Genome-wide association between branch point properties and alternative splicing. by André Corvelo, Martina Hallegger, Christopher W J Smith, Eduardo Eyras

“…Using a Support Vector Machine algorithm, we created a model complemented with polypyrimidine tract features, which considerably improves the prediction accuracy over previously published methods. …”
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Intelligence model-driven multi-stress adaptive reliability enhancement testing technology by Shouqing Huang, Beichen He, Jing Wang, Xiaoyang Li, Rui Kang, Fangyong Li

“…In terms of mathematical models, we propose a Tuna Swarm Optimization–Gaussian Process Regression (TSO-GPR) model, which combines the global search capability of the tuna swarm optimization algorithm and the accurate prediction capability of Gaussian process regression, effectively handling the complex nonlinear relationships between multiple stresses and failure characteristic. …”
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Comprehensive Analysis of the Role of Metabolic Features in Osteoporosis: A Multi-Omics Analysis by Chang S, Tao W, Shi P, Wu H, Liu H, Xu J, Chen J, Zhu J

“…Additionally, 13 differentially expressed TFs were predicted to regulate the expression levels of these 23 miRNAs. …”
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RESULTS OF USTEKINUMAB TREATMENT IN PATIENTS WITH PSORIATIC ARTHRITIS IN THE RUSSIAN FEDERATION ACCORDING TO THE DATA OF PSUMMIT 1 AND PSUMMIT 2 by Yu. L. Korsakova, A. A. Godzenko, A. O. Pchelintseva, O. Yu. Grigoryeva, L. N. Denisov, E. L. Nasonov

“…After 16 weeks the patients showing a less than 5% reduction  in the number of tender and swollen joints were given UST 45 mg (if they belonged to the PL group) or 90 mg (if they were in the UST 45-mg group). …”
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Autoconcepto físico en estudiantes universitarios: Generación de perfiles por clasificación jerárquica sobre componentes principales (Physical self-concept in university students:... by Luis Alberto Cardozo, Jhonatan C. Peña-Ibagón, Widad Florez-Escobar, Carlos A. Castillo-Daza, Diego A. Bonilla-Ocampo, Javier L. Reina-Monroy

“…The aims of this study were i) to analyze and compare the physical self-concept in university students considering possible differences between sexes and associations with socioeconomic status and age, and ii) to generate student profiles using unsupervised machine learning algorithms. A total of 230 Colombian students between 18 and 38 years of age from the Physical Education (n = 118) and Psychology (n = 112) majors participated in this cross-sectional study. …”
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MATHCAD APPLICATION FOR THE MULTIDIMENSIONAL ANALYSIS OF THE INTERDEPENDENCES ON WORLD STOCK MARKETS by Marina A. Skorik, Andrey G. Nefedov

“…Its usage in the educational process allows to develop stable skills in applying of mathematical and statistical methods of data analysis.…”
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Generation of Spatial Structure of Urban Parks Based on Spatial Analysis of Agent-Based Models by Huizi KONG, Tianming LIU, Jiajie LIAO, Liu CUI

“…ObjectiveThis research aims to leverage the advances of computer algorithms to provide scientific analytical methods for spatial simulation and offer a more objective approach to reflect the natural operational laws of interdependencies between elements in the real physical world for landscape design. …”
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