Outpatient diagnosis of endogenous intoxication in surgery by A. A. Solomakha, A. P. Vlasov, V. I. Gorbachenko

“…The problems of diagnosis, treatment, prevention and prediction of purulent diseases in surgery can be solved thanks to advanced digital technologies.Aim of the study. …”
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Molecular insights into ulcerative colitis and orbital inflammation by Kang Tan, Pei Liu, Zixuan Wu, Xi Long, Yunfeng Yu, Pengfei Jiang, Qinghua Peng

“…GO enrichment, PPI networks, and transcription factor prediction were performed using Cytoscape plugins (cytoHubba and iRegulon). …”
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Computational Intelligence-Based Structural Health Monitoring of Corroded and Eccentrically Loaded Reinforced Concrete Columns by Somain Sharma, Harish Chandra Arora, Aman Kumar, Denise-Penelope N. Kontoni, Nishant Raj Kapoor, Krishna Kumar, Arshdeep Singh

“…Machine learning (ML)-based prediction models are beneficial in dealing with such complex databases. …”
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Experimental investigation of shaft misalignment effects on bearing reliability through vibration signal analysis using machine learning and deep learning by Fransiskus Tatas Dwi Atmaji, Jamasri, Hari Agung Yuniarto, I Made Miasa

“…Despite its practical importance, the direct impact of parallel shaft misalignment on bearing fault prediction remains unaddressed, mainly in the existing literature. …”
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Genomic profiling, implications for genotype-based treatment of 131 patients with phenylketonuria and characterization of novel p.Pro416Leu PAH variant by K. Klaassen, B. Kecman, S. Stankovic, J. Komazec, S. Pavlovic, Maja Stojiljkovic, M. Djordjevic

“…We detected one novel variant, p.Pro416Leu, which was classified as pathogenic, based on computational algorithms prediction, with destabilization as the mechanism of the effect upon PAH protein. …”
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Integrating Machine Learning Workflow into Numerical Simulation for Optimizing Oil Recovery in Sand-Shale Sequences and Highly Heterogeneous Reservoir by Dung Bui, Abdul-Muaizz Koray, Emmanuel Appiah Kubi, Adewale Amosu, William Ampomah

“…A machine learning-based proxy model was built for the prediction of cumulative oil production and then optimized with hybrid machine learning techniques. …”
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Tactical Coordination-Based Decision Making for Unmanned Combat Aerial Vehicles Maneuvering in Within-Visual-Range Air Combat by Yidong Liu, Dali Ding, Mulai Tan, Yuequn Luo, Ning Li, Huan Zhou

“…The former combines missile attack zone calculation and trajectory prediction to optimize the control quantity of a single aircraft, while the latter uses fuzzy logic to analyze the overall situation of the three aircraft to drive tactical selection. …”
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A Scale‐Adaptive Urban Hydrologic Framework: Incorporating Network‐Level Storm Drainage Pipes Representation by Taher Chegini, Hong‐Yi Li, Y. C. Ethan Yang, Günter Blöschl, L. Ruby Leung

“…Furthermore, analysis reveals nonlinear relationships between BUSNs' designed capacities and flood reduction effects. Our approach bridges the gap between detailed hydraulic and large‐scale hydrologic models, providing a valuable tool for urban flood prediction and management across broader spatial and temporal scales.…”
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Liquid biopsy-derived extracellular vesicle protein biomarkers for diagnosis and prognostic assessment of lung squamous cell carcinoma by Sheng Ma, Na Zhao, Xin Dong, Yaru Wang, Lei Song, Ruiqi Zheng, Xiaochen Zhi, Congcong Ma, Shujun Cheng, Jie Li, Yutao Liu, Ting Xiao

“…Additionally, a prognostic prediction model for LUSC was developed using a combination of 101 machine learning algorithms. …”
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Discovering biomarkers associated with infiltration of CD8+ T cells and tumor-associated fibrosis in colon adenocarcinoma using single-cell RNA sequencing and gene co-expression ne... by Jinning Zhang, Jinning Zhang, Ziquan Sun, Ziquan Sun, Guodong Li, Guodong Li, Lixian Ding, Zitong Wang, Ming Liu, Ming Liu

“…We utilized univariate Cox regression and LASSO analysis to create a prognostic model. The predictive model was assessed through Kaplan-Meier analysis, and a survival prediction nomogram was created. …”
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Neural Network-Based Imitation Learning for Approximating Stochastic Battery Management Systems by Andrea Pozzi, Alessandro Incremona, Daniele Toti

“…While stochastic predictive control policies can address these uncertainties by incorporating them directly into the optimization process, they typically introduce considerable computational complexity. …”
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Forecast of Photovoltaic Power Based on IWPA-LSSVM Considering Weather Types and Similar Days by Yilun XU, Binqiao ZHANG, Jing HUANG, Xiao XIE, Ruoxin WANG, Danqing SHEN, Lina HE, Kaifan YANG

“…In order to improve the prediction accuracy of photovoltaic power, the input of the photovoltaic power prediction model is determined according to the characteristics of photovoltaic output power under different weather types. …”
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Special Issue on Contemporary Research Studies in Operations Research, Business Analytics, and Business Intelligence by Viswanath Kumar Ganesan, S. Vinodh, Malolan Sundararaman, M. Vimala Rani, M. Mathirajan

“…Advanced Scheduling Algorithms: Creating advanced meta-heuristic algorithms using efficient dispatching rule-based heuristics for dynamic scheduling of non-identical parallel batch processing machines with eligibility constraints. 8. …”
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Large Language Models and Artificial Neural Networks for Assessing 1-Year Mortality in Patients With Myocardial Infarction: Analysis From the Medical Information Mart for Intensive... by Boqun Shi, Liangguo Chen, Shuo Pang, Yue Wang, Shen Wang, Fadong Li, Wenxin Zhao, Pengrong Guo, Leli Zhang, Chu Fan, Yi Zou, Xiaofan Wu

“…An artificial neural network (ANN) algorithm derived from the SWEDEHEART (Swedish Web System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies) registry, termed SWEDEHEART-AI, can predict patient prognosis following acute myocardial infarction (AMI). …”
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Research on Management Model Based on Deep Learning by Yuting Zhao

“…In this study, the focus was on the development of management models and future prediction for the cost and risk by using an improved deep learning (DL) algorithm. …”
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Practical aspects of therapy for glutaric aciduria type 1 by E. Yu. Zakharova, S. V. Mikhailova, V. V. Zarubina, N. A. Krasnoshchekova, N. L. Pechatnikova, V. P. Vorontsova, D. I. Gribov, M. V. Zazivihina, А. N. Slatetskaya, M. V. Kurkina, P. V. Baranova, L. P. Nazarenko, S. А. Repina, L. R. Selimsyanova, N. D. Vashakmadse, T. V. Bushueva

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Estimation and trend analysis of grassland aboveground biomass on the Qinghai-Xizang Plateau based on machine learning by Ruoqi Zhang, Qisheng Feng, Yonghui Zhang, Jingjing Mai, Tiangang Liang

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Implementasi Algoritma Catboost Dan Shapley Additive Explanations (SHAP) Dalam Memprediksi Popularitas Game Indie Pada Platform Steam by Mohammad Teddy Syamkalla, Siti Khomsah, Yohani Setya Rafika Nur

“…The SHAP method reveals the influence of features on prediction results. The existence of steam trading cards category, RPG genre and compatibility on mac operating system will increase the popularity. …”
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Development of a circadian-related prognostic signature highlights RBM17 as a stemness regulator in liver cancer by Jingsong Yan, Xiao Yang, Jiabin Lu, Shasha Wu, Yanchen Wang, Yuyang Du, Jingyi Zheng, Fenfen Wang, Han Gao, Hui Yang, Shaoyan Xi, Yan Li

“…Our research aims to elucidate these mechanisms and develop a predictive model for prognosis and treatment responsiveness. …”
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Unraveling the role of histone acetylation in sepsis biomarker discovery by Feng Cheng, Juxin Deng, Zhaoyang Du, Lei Li, Zhaolei Qiu, Min Zhu, Hongchang Zhao, Hongchang Zhao, Zhenjie Wang, Zhenjie Wang

“…Mendelian randomization (MR), RT-qPCR, and functional assays were conducted for validation.ResultsBLOC1S1, NDUFA1, and SFT2D1 were identified as key biomarkers. A predictive nomogram demonstrated strong diagnostic potential. …”
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