Fluvial bedload transport modelling: advanced ensemble tree-based models or optimized deep learning algorithms? by Khabat Khosravi, Aitazaz A. Farooque, Sayed M. Bateni, Changhyun Jun, Dorsa Mohammadi, Zahra Kalantari, James R. Cooper

“…The potential of advanced tree-based models and optimized deep learning algorithms to predict fluvial bedload transport was explored, identifying the most flexible and accurate algorithm, and the optimum set of readily available and reliable inputs. …”
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Integrated Machine Learning and Region Growing Algorithms for Enhanced Concrete Crack Detection: A Novel Approach by Wenxuan Yao, Hui Li, Yanlin Li

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Machine learning as a tool for diagnostic and prognostic research in coronary artery disease by B. I. Geltser, M. M. Tsivanyuk, K. I. Shakhgeldyan, V. Yu. Rublev

“…The advantages and disadvantages of individual ML methods (logistic regression, support vector machines, decision trees, naive Bayesian classifier, k-nearest neighbors) for the development of diagnostic and predictive algorithms are shown. The most promising ML methods include deep learning, which is implemented using multilayer artificial neural networks. …”
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Development and validation of a machine learning-based survival prediction model for Asian glioblastoma patients using the SEER database and Chinese data by Denglin Li, Luxin Zhang, Lifei Xu, Renhe Zhai, Hanyu Gao, Junlan Gao, Minghai Wei, Ningwei Che, Yeting He

“…Our study attempted to investigate the independent predictors of overall survival (OS) and cancer-specific survival (CSS) in Asian patients with glioblastoma and establish predictive models for the OS and CSS of Asian patients with glioblastoma based on the machine learning algorithms. …”
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A comparative analysis of imaging-based algorithms for detecting focal cortical dysplasia type II in children by Jan Šanda, Zuzana Holubová, David Kala, Kateřina Jiránková, Martin Kudr, Tomáš Masák, Anežka Bělohlávková, Pavel Kršek, Jakub Otáhal, Martin Kynčl

“…The junction algorithm achieved the highest median dice score (0.028, IQR 0.038, p < 0.01 when compared with other algorithms) and detected relevant clusters even in MRI-negative cases. …”
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Maize crop residue cover mapping using Sentinel-2 MSI data and random forest algorithms by Jia Du, Pierre-Andre Jacinthe, Kaishan Song, Longlong Zhang, Boyu Zhao, Hua Liu, Yan Wang, Weijian Zhang, Zhi Zheng, Weilin Yu, Yiwei Zhang, Dapeng Jiang

“…The tillage indices with the best predictive performance were STI and NDTI (R2 of 0.85 and 0.84, respectively). …”
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Urban building-level positioning using data-driven algorithms enhanced by spatial variations in sensor features by Die Zhang, Xin Liu, Yong Ge, Yixi Wei, Mengxiao Liu

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Evaluating the impact of industrial wastes on the compressive strength of concrete using closed-form machine learning algorithms by Carlos Roberto López Paredes, Cesar García, Kennedy C. Onyelowe, Kennedy C. Onyelowe, Maria Gabriela Zuniga Rodriguez, Tammineni Gnananandarao, Alexis Ivan Andrade Valle, Nancy Velasco, Greys Carolina Herrera Morales

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Predicting onset of myopic refractive error in children using machine learning on routine pediatric eye examinations only by Yonina Ron, Tchelet Ron, Naomi Fridman, Anat Goldstein

“…Among them, 429 (11%) developed myopia. The models predicted myopia with up to 77% sensitivity and 92% specificity. …”
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Enhanced safety and efficiency in traction elevators: a real-time monitoring system with anomaly detection by Safa Ozdemir, Osamah N. Neamah, Raif Bayir

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Surveying the knowledge of pregnant women towards sport activities during pregnancy using data mining algorithms by Fatemeh Bagherı, Fatemeh Islamı, Fatemeh Mohammadı

“…In predicting the level of knowledge using decision tree in both prediction level (5 label and 3 label), C5.0 algorithm had the most accurate prediction. …”
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Designing Predictive Analytics Frameworks for Supply Chain Quality Management: A Machine Learning Approach to Defect Rate Optimization by Zainab Nadhim Jawad, Balázs Villányi

“…The framework employs advanced ML algorithms, including extreme gradient boosting (XGBoost), support vector machines (SVMs), and random forests (RFs), to accurately predict defect rates and derive actionable insights for supply chain optimization. …”
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A Talent Training Model for Electrical Courses considering Diverse Constraint Models and Knowledge Recognition Algorithms by Fanping Min

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Application of Artificial Intelligence Technology in Martial Arts Education Governance by Weiwu Ye, Shihong Li, Shuaibing Liu, Yuan Zhou

“…It greatly simplifies the prediction of key points and solves the problem of nonstandard movements of students in martial arts education. …”
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Machine learning unveils hypoxia-immune gene hub for clinical stratification of thyroid-associated ophthalmopathy by Lu Chen, Sha Wang, Jinwei Wang, Bei Xu, Jia Tan, Xiaobo Xia

“…Hypoxia exposure aggravated the above dysregulation and promoted proliferation and adipogenesis of orbital fibroblasts. A predictive model was developed using four machine learning algorithms and validated for its effectiveness in diagnosing TAO and assessing disease severity. …”
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Associations of DNA Methylation Algorithms of Aging With Cardiovascular Disease and Mortality Risk Among US Older Adults by Xian Cui, Shiqun Sun, Hui Zhang, Yulu Gong, Darong Hao, Yaqian Xu, Chongyu Ding, Jing Wang, Tongyan An, Jinlong Liu, Jun Du, Xiangwei Li

“…However, their predictive performance for CVD varies significantly. …”
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Models of the Impact of Socio-Economic Shocks on Higher Education Development by Olena Rayevnyeva, Volodymyr Ponomarenko, Silvia Matusova, Kostyantyn Stryzhychenko, Stanislav Filip, Olha Brovko

“…An algorithmic model for studying the impact of social and economic shocks on the development of the higher education system (HES) has been developed. …”
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Educational Data Mining by Optimally Fusing Shallow and Deep Features by Bo-An Xiao

“…In order to meet the requirement of designing the educational curriculum and extract the relevant data toward students, we in this paper utilize the deep learning architecture to study the personalized understanding and educational feature extraction algorithm of the high school and college students. …”
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Preparation for Entering a Higher Educational Institution as an Investment Project by V. A. Kataeva, V. R. Masalkina, A. A. Ponomareva

“…The purpose of the study is to develop an algorithm for managing investments in preparation for entering a higher educational institution as an investment project.Materials and methods. …”
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Reconsidering the use of race, sex, and age in clinical algorithms to address bias in practice: A discussion paper by Reanna Panagides, Jessica Keim-Malpass

“…Clinical algorithms are commonly used as decision-support tools, incorporating patient-specific characteristics to predict health outcomes. …”
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