Functional Complete Revascularization as Determined by an Optimized Scoring System After Revascularization: A Post Hoc Analysis from Multi‐Center PANDA III Trial by Rui Zhang, Shaoyu Wu, Qianqian Liu, Changdong Guan, Hao‐Yu Wang, Sheng Yuan, Lihua Xie, Yunfei Huang, Zheng Qiao, Weida Liu, Rui Fu, Lei Feng, Chenggang Zhu, Lei Song, Dong Yin, Kefei Dou

“…The m‐rFSS is more predictive of 2‐year MACE than c‐rFSS (difference in C‐index 0.07, p < 0.001). …”
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Draft genome dataset of Streptomyces griseoincarnatus strain R-35 isolated from tidal pool sedimentsMendeley DataNCBI by Danielle Dana Mitchell, Jo-Marie Vreulink, Alaric Prins, Marilize Le Roes-Hill

“…The phylogenomic positioning of S. griseoincarnatus strain R-35 was determined using the Type Strain Genome Server (TYGS) and was found to be related to S. griseoincarnatus JCM 4381T, with a digital DNA-DNA hybridisation (dDDH) value of 84.1%, and an OrthoANIu value of 98.22%. The CARD RGI algorithm on Proksee predicted the presence of 6,107 antimicrobial resistance (AMR) features, 27 biosynthetic gene clusters (BGCs) were predicted using antiSMASH, while 189 carbohydrate-active enzymes (CAZymes) were predicted using dbCAN3. …”
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Preoperative assessment of tertiary lymphoid structures in stage I lung adenocarcinoma using CT radiomics: a multicenter retrospective cohort study by Xiaojiang Zhao, Yuhang Wang, Mengli Xue, Yun Ding, Han Zhang, Kai Wang, Jie Ren, Xin Li, Meilin Xu, Jun Lv, Zixiao Wang, Daqiang Sun

“…Tumor segmentation was achieved using an automatic virtual adversarial training segmentation algorithm based on a three-dimensional U-shape convolutional neural network (3D U-Net). …”
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The association between inflammatory, metabolic, and hepatic fibrosis-related biomarkers and atrial fibrillation in older patients with metabolic dysfunction-associated steatotic l... by Shuai Zhang, Hao Liang, Jun Liu, Zhipeng Huang, Xijing Shi, Ye Zhu

“…The variable importance ranking results based on the Boruta algorithm, as well as the Receiver Operating Characteristic (ROC) curve and Decision Curve Analysis (DCA), all indicate that NFS and ALBI have high predictive performance and clinical benefits. …”
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Life cycle assessment and multicriteria decision making analysis of additive manufacturing processes towards optimal performance and sustainability by Jayant M. Raut, Prashant B. Pande, Kamlesh V. Madurwar, Rajesh M. Bhagat, Satyajit S. Uparkar, Nilesh Shelke, Haytham F. Isleem, Arpita, Vikrant S. Vairagade

“…Experimental results prove that predictive accuracy can be achieved up to 85–90% by GPR, which reduces material wastage by 12%. …”
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Statistical Evaluation of Smartphone-Based Automated Grading System for Ocular Redness Associated with Dry Eye Disease and Implications for Clinical Trials by Rodriguez JD, Hamm A, Bensinger E, Kerti SJ, Gomes PJ, Ousler III GW, Gupta P, De Moraes CG, Abelson MB

“…The model utilizes the DeepLabV3 architecture for image segmentation, extracting two key features—horizontality and redness. The algorithm then uses these features to predict eye redness, validated by comparison with expert grader scores.Results: The bivariate model using both redness and horizontality performed best, with a Mean Absolute Error (MAE) of 0.450 points (SD=0.334) on the redness scale relative to expert scores. …”
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Modeling of Interactive Teaching and Learning System for Students Based on Artificial Intelligence by Jiaming Liu, Han Zou

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Driver injury severity in two-vehicle accidents considering collision role by JIN Wenzhou, PEI Xiaohang, TANG Zuogan, YAO Yinjie

“…In order to study the influencing factors of driver injury severity and the interaction effects of collision roles in two-vehicle accidents, based on the data of two-vehicle collision accidents in Shenzhen from 2018 to 2020, we calculate the value of importance degree of characteristic variables by using random forest algorithm to screen out the candidate independent variables, and establish a binary logit model of driver injury severity considering collision angle. …”
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Analysis of Fuzzy Logic Modification for Student Assessment in e-Learning by Retantyo Wardoyo, Wenty Dwi Yuniarti

“…This study presents an analysis of fuzzy logic modification for the assessment of Algorithm and Data Structures courses held in e-Learning. …”
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Validation of CT perfusion-based vascular territory mapping: correlation to visual pial grading and outcome measures by Michael Valente, Henry Ma, Andrew Bivard, Bernard Yan, Mark Parsons, Chushuang Chen, Milanka Visser

“…VTM variables were not predictive of anterior collateral grade or stroke outcome measures. …”
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A hybrid AI-CFD framework for optimizing heat transfer of a premixed methane-air flame jet on inclined surfaces by Panit Kamma, Kittipos Loksupapaiboon, Juthanee Phromjan, Chakrit Suvanjumrat

“…To reduce the computational expense of these simulations, a hybrid Artificial Neural Network-Genetic Algorithm (ANN-GA) model was developed. The ANN accurately predicted thermal efficiency based on operational parameters, while the GA optimized these inputs to achieve maximum thermal efficiency of 76.9955 %, closely matching the CFD-predicted value of 70.86 % (discrepancy:6.1355 %). …”
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Pilot Allocation in Multi-Cell MIMO Systems Based on Missing Data Imputation by Bushra Shaikh, Pere Garau Burguera, Hanan Al-Tous, Markku Juntti, Bilal Muhammad Khan, Olav Tirkkonen

“…We consider a pilot allocation algorithm to alleviate pilot contamination in a multi-cell massive MIMO network with missing channel information. …”
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Big data and data science in global governance: anticipating future needs and applications in the UN and beyond by Lanxin Li, Jiarou Wang, Xi Wang, Peng Peng, Jiaying Shen, Haining Zhu, Ziyang Zhang

“…The research identifies the “4Vs” of big data (Volume, Velocity, Variety, and Veracity) as fundamental characteristics reshaping governance approaches while highlighting innovative applications like UN Global Pulse, SDG tracking systems, and AI-driven predictive analytics in crisis prevention. We assess technical, ethical, and organizational challenges, including data quality inconsistencies, interoperability issues, privacy concerns, algorithmic bias, and resource constraints that impede the full integration of big data into governance systems. …”
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Genome‐scale metabolic modeling reveals SARS‐CoV‐2‐induced metabolic changes and antiviral targets by Kuoyuan Cheng, Laura Martin‐Sancho, Lipika R Pal, Yuan Pu, Laura Riva, Xin Yin, Sanju Sinha, Nishanth Ulhas Nair, Sumit K Chanda, Eytan Ruppin

“…We next applied the GEM‐based metabolic transformation algorithm to predict anti‐SARS‐CoV‐2 targets that counteract the virus‐induced metabolic changes. …”
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Removal mechanism and damage evolution of SiCp/Al composites based on FEM-MD model considering 3D random polyhedral particles in orthogonal cutting by Ming Li, Qingguang Li, Xianchao Pan, Jiaqi Wang, Zixuan Wang, Shengzhi Xu, Yunguang Zhou, Lianjie Ma, Tianbiao Yu

“…Experimental validation confirmed the multi-scale model's predictive accuracy for machining-induced surface damage. …”
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Utility of Domain Adaptation for Biomass Yield Forecasting by Jonathan M. Vance, Bryan Smith, Abhishek Cherukuru, Khaled Rasheed, Ali Missaoui, John A. Miller, Frederick Maier, Hamid Arabnia

“…A novel technique is proposed for forecasting alfalfa time series data that exploits stationarity and predicts differences in yields rather than the yields themselves. …”
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Artificial intelligence for screening and early diagnosis of pancreatic neoplasms in the context of centralization of the laboratory service in the region by S. I. Panin, V. A. Suvorov, A. V. Zubkov, S. A. Bezborodov, A. A. Panina, N. V. Kovalenko, A. R. Donsckaia, I. G. Shushkova, A. V. Bykov, Ya. A. Marenkov

“…A comparative assessment of machine learning techniques showed that the best option for creating the appropriate software was Hist Gradient Boosting (diagnostic accuracy 0.909, sensitivity 0.642, specificity 0.965, negative predictability 0.928, positive predictability 0.794, F1 0.828, logistic regression loss function 0.352, area under the ROC curve 0.89). …”
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A comparative approach of analyzing data uncertainty in parameter estimation for a Lumpy Skin Disease model by Edwiga Renald, Miracle Amadi, Heikki Haario, Joram Buza, Jean M. Tchuenche, Verdiana G. Masanja

“…The assessment of the uncertainties is determined with the help of Adaptive Metropolis Hastings algorithm, a Markov Chain Monte Carlo (MCMC) standard statistical method. …”
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An integrated Artificial neural network technique to optimize the various parameters of Pineapple/SiO2/epoxy-based nanocomposites under NaOH treatment by Natrayan Lakshmaiya, Naga Dheeraj Kumar Reddy Chukka, Seeniappan Kaliappan, V. Balaji, Nimel Sworna Ross, Ramya Maranan

“…Quantitative optimisation using the Taguchi technique Depending on the S/N ratio of Taguchi refinement, the nanocomposite with the maximum mechanical performance contains 20 % pineapple fibre with a length of 10 mm, 5 % nano SiO2, and 6 h of NaOH treatment. The ANN predictive algorithm and the Taguchi L27 array show that the experiment and projected data for tensile, flexural, and impact are within 3 % and 4 %. …”
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Construction of a prognostic model based on memory CD4+ T cell–associated genes for lung adenocarcinoma and its applications in immunotherapy by Yong Li, Xiangli Ye, Huiqin Huang, Rongxiang Cao, Feijian Huang, Limin Chen

“…In this study, using the cell‐type identification by estimating relative subsets of RNA transcripts algorithm, we analyzed immune cell composition and patient survival in LUAD. …”
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