Control of Overfitting with Physics by Sergei V. Kozyrev, Ilya A. Lopatin, Alexander N. Pechen

“…An application of this analogy allows us to explain the selection of wide likelihood maxima and ab overfitting reduction for GANs.…”
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Entire aerial-aquatic trajectory modeling and optimization for trans-medium vehicles by Teng Long, Nianhui Ye, Baoshou Zhang, Jingliang Sun, Renhe Shi

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Artificial intelligence-based Bayesian optimization and transformer model for tennis motion recognition by Shaowei Shi, Kun Huang

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College English Audio-Visual-Oral Teaching Mode from the Perspective of Artificial Intelligence by Li Ling

“…The “New Era Artificial Brain Power Improvement Plan” issued by the State Council and the “Computer Reasoning Development Activity Plan for Colleges and Universities” issued by the Ministry of Education clearly pointed out that it is necessary to attach importance to the combination of modern education and artificial intelligence. …”
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Screening biomarkers related to cholesterol metabolism in osteoarthritis based on transcriptomics by ChenDeng Lao, Wei Wei, JianWen Cheng, ShiJie Liao, XiaoLin Luo, Qian Huang, HengZhen Huang, JinMin Zhao

“…Three machine learning algorithms identified ATF3, CHKA, CLU, CTNNB1, and FASN as potential biomarkers. …”
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Optimization of Flight Scheduling in Urban Air Mobility Considering Spatiotemporal Uncertainties by Lingzhong Meng, Minggong Wu, Xiangxi Wen, Zhichong Zhou, Qingguo Tian

“…Traditional flight plan adjustment and management methods often rely on deterministic trajectory predictions, ignoring the inherent temporal uncertainties in actual operations, which may lead to the underestimation of potential risks. …”
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A Novel Approach for Maize Straw Type Recognition Based on UAV Imagery Integrating Height, Shape, and Spectral Information by Xin Liu, Huili Gong, Lin Guo, Xiaohe Gu, Jingping Zhou

“…Accurately determining the distribution and quantity of maize straw types is of great significance for evaluating the effectiveness of conservation tillage, precisely estimating straw resources, and predicting the risk of straw burning. The widespread adoption of conservation tillage technology has greatly increased the diversity and complexity of maize straw coverage in fields after harvest. …”
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RETRACTED ARTICLE: Single-cell omics and machine learning integration to develop a polyamine metabolism-based risk score model in breast cancer patients by Xiliang Zhang, Hanjie Guo, Xiaolong Li, Wei Tao, Xiaoqing Ma, Yuxing Zhang, Weidong Xiao

“…These genes were analyzed using univariate COX and machine learning algorithms to develop a prognostic scoring algorithm. …”
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Thrombotic Lesion of the Pulmonary Vessels in Patients with Pulmonary Embolism by A. A. Klimenko, N. A. Demidova, N. A. Shostak, M. O. Anischenko

“…Pathogenetic aspects of this condition are not fully investigated. It is important to predict the development of postembolic syndrome and to develop algorithms for the diagnosis, treatment and rehabilitation of patients with symptoms and residual pulmonary thrombosis. …”
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Feasibility and case studies on converting small hydropower stations to pumped storage by Yangqing Dan, Qingyue Chen, Daren Li, Wenhuan Bai, Weiming Zhou, Anyu Yang, Jia Yang

“…The proposed conversion scheme has been assessed, and predictions regarding annual operating hours, power generation, and energy consumption have been formulated. …”
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Investigation of granuloma-targeted host-pathogen interactions identify vaccine correlates of immune protection associated with control of M. tuberculosis replication by David Forrest Ackart, Dr. Faye Lanni, Victoria Mitcham, Dr. G. Brooke Anderson, Dr. Michael Lyons, Dr. Marcela Henao-Tamayo, Dr Brendan Podell

“…While a number of blood transcriptomic signatures have been shown to predict clinical states of TB in human subjects, no correlates exist to indicate immune signatures that control bacterial growth, which would inform improved vaccine design. …”
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Trends in Russia’s GDP Growth under Environmental Constraints by Z. V. Bragina, A. R. Denisov, N. N. Masyuk, N. V. Steblyanskii

“…Methods used: empirical and statistical analysis, building regression models, algorithmic and predictions, building time trends, etc. …”
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Novel estrogen-related gene variants identified by whole-exome sequencing in pregnancy-associated intrahepatic cholestasis by Hua Lai, Siming Xin, Jinliang Zhang, Yang Hu, Wenjuan Fan, Hong Wan, Bowen Chen, Yang Zou, Xiaoming Zeng, Xianxian Liu

“…These variants exhibited the following characteristics: (1) complete absence in 1,237 controls and all public genomic databases (1000 Genomes, ExAC, and dbSNP); (2) evolutionary conservation of the affected residues, with unanimous pathogenic predictions from all algorithms (PolyPhen-2: damaging; SIFT: deleterious; MutationTaster: disease-causing); (3) molecular modeling demonstrating structural perturbations in critical functional domains, including steroid-binding and redox partner interaction sites. …”
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Federated Learning Based on an Internet of Medical Things Framework for a Secure Brain Tumor Diagnostic System: A Capsule Networks Application by Roman Rodriguez-Aguilar, Jose-Antonio Marmolejo-Saucedo, Utku Köse

“…The precision rate indicates that the CapsNet model performs well in accurately predicting true classes. Additionally, the recall findings suggest that this model is effective in detecting the target classes of meningiomas, pituitary tumors, and gliomas. …”
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Exploration of Biomarkers of Psoriasis through Combined Multiomics Analysis by Lu Xing, Tao Wu, Li Yu, Nian Zhou, Zhao Zhang, Yunjing Pu, Jinnan Wu, Hong Shu

“…The druggable genes were predicted using DGIdb. Finally, the expressions of hub genes in psoriasis lesions and healthy controls were detected by immunohistochemistry (IHC) and quantitative real-time PCR (RT-qPCR). …”
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Machine learning−derived multivariable predictors of postcardiotomy cardiogenic shock in high-risk cardiac surgery patientsCentral MessagePerspective by Edward G. Soltesz, MD, MPH, Randi J. Parks, PhD, Elise M. Jortberg, MS, Eugene H. Blackstone, MD

“…Objective: To develop a model for preoperatively predicting postcardiotomy cardiogenic shock (PCCS) in patients with poor left ventricular (LV) function undergoing cardiac surgery. …”
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Machine learning developed LKB1-AMPK signaling related signature for prognosis and drug sensitivity in hepatocellular carcinoma by Wang Li, Xiaoyi Zhu, Jieying Fang

“…Our investigation developed a novel LRS for HCC, serving as an indicator for predicting clinical outcome and immunotherapy response.…”
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Performance evaluation and multi-objective optimization of EDM parameters for Ti6Al4V using different tool electrodes by Manoj Jagdale, Masuk Abdullah, Nitin Ambhore, Atul Kulkarni, Rakesh Chaudhari, Jay Vora, József Menyhárt

“…A minor adequate deviance was observed between the TLBO algorithm’s predicted and actual findings. Scanning electron microscopy (SEM) analysis was conducted to evaluate surface morphology. …”
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Supervised machine learning and genotype by trait biplot as promising approaches for selection of phytochemically enriched Rhus coriaria genotypes by Hamid Hatami Maleki, Reza Darvishzadeh, Ahmad Alijanpour, Yousef Seyfari

“…By using 13 feature selection algorithms, ISSR loci (U823) L1, (U835) L1, (U801) L1, (U816) L2, (U816) L4, (U835) L4, (U854) L1, and (U835) L9 were identified as functional markers which could predict phytochemical response of sumac germplasm. …”
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Design and Development of Diabetes Management System Using Machine Learning by Robert A. Sowah, Adelaide A. Bampoe-Addo, Stephen K. Armoo, Firibu K. Saalia, Francis Gatsi, Baffour Sarkodie-Mensah

“…The model achieved specified goals by predicting with high accuracy, labels of new images. …”
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