Clinical Outcome Prediction Model in Tetralogy of Fallot Without Pulmonary Valve Replacement Using Contraction Fraction From the SCOUT‐TOF Registry by Mark A. Fogel, Jennifer A. Faerber, Abdullah Mahmood, Keerthi Reddy, Xuemei Zhang, Elizabeth Goldmuntz, Matthew A. Harris, David Biko, Sara Partington, Stephen Paridon, Michael Mcbride, Victor Ferrari, Kevin K. Whitehead, Laura Mercer‐Rosa

“…Methods and Results We retrospectively reviewed cardiac magnetic resonance parameters of patients with rTOF undergoing cardiac magnetic resonance from 2005 to 2021. Composite outcome 1 (CO1) included death, transplantation, ventricular tachycardia, and pacemaker placement, and composite outcome 2 (CO2) added cardiovascular hospitalizations. …”
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Association between triglyceride-glucose related indices and at-risk NASH in U.S. adults with NAFLD: results from NHANES 2017-2020 by Hanchen Ma, Wenjie Zhang, Wenjie Zhang, Zheng Zhao, Shuaichen Jin, Linchuan Li, Linchuan Li, Ruizhao Zong, Ruizhao Zong, Wuyang Li, Wuyang Li, Ziwei Zhang, Ziwei Zhang, Shichang Cui, Shichang Cui, Yunmiao Pan, Jiankang Zhu, Jiankang Zhu, Guangyong Zhang, Guangyong Zhang, Guangyong Zhang

“…RCS analysis revealed no significant nonlinear relationships in composite indices, whereas the TyG index demonstrated a significant nonlinear association. …”
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The chronic heart failure evolutions: Different fates and routes by Piergiuseppe Agostoni, Mattia Chiesa, Elisabetta Salvioni, Michele Emdin, Massimo Piepoli, Gianfranco Sinagra, Michele Senni, Alice Bonomi, Stamatis Adamopoulos, Dimitris Miliopoulos, Massimo Mapelli, Jeness Campodonico, Umberto Attanasio, Anna Apostolo, Emanuele Pestrin, Agostino Rossoni, Damiano Magrì, Stefania Paolillo, Ugo Corrà, Rosa Raimondo, Antonio Cittadini, Annamaria Iorio, Andrea Salzano, Rocco Lagioia, Carlo Vignati, Roberto Badagliacca, Pasquale Perrone Filardi, Michele Correale, Enrico Perna, Marco Metra, Gaia Cattadori, Marco Guazzi, Giuseppe Limongelli, Gianfranco Parati, Fabiana De Martino, Maria Vittoria Matassini, Francesco Bandera, Maurizio Bussotti, Federica Re, Carlo M. Lombardi, Angela B. Scardovi, Susanna Sciomer, Andrea Passantino, Caterina Santolamazza, Davide Girola, Claudio Passino, Marlus Karsten, Savina Nodari, Giulio Pompilio, MECKI score research group

“…Finally, we conducted a 5‐year survival analysis (composite of cardiovascular death, left ventricular assist device, or urgent heart transplant). …”
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Cardiac magnetic resonance left atrioventricular coupling index as a prognostic tool in hypertrophic cardiomyopathy by Jinyang Wen, Junhao Tu, Xinwei Tao, Yuanyuan Tang, Zhaoxia Yang, Ziyi Pan, Yi Luo, Chunlin Xiang, Dazhong Tang, Lu Huang, Liming Xia

“…In the multivariate Cox regression analysis, LACI [hazard ratio 1.054, 95% confidence interval (CI): 1.037, 1.071; P < 0.001] was an independent predictor of the composite events after adjustment for age and atrial fibrillation. …”
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Development and Validation of a Machine Learning Prediction Model for Textbook Outcome in Liver Surgery: Results From a Multicenter, International Cohort by Jane Wang, MD, Amir Ashraf Ganjouei, MD, MPH, Taizo Hibi, MD, PhD, Nuria Lluis, MD, PhD, Camilla Gomes, MD, Fernanda Romero-Hernandez, MD, Han Yin, BA, Lucia Calthorpe, MD, Yukiyasu Okamura, MD, PhD, Yuta Abe, MD, PhD, Shogo Tanaka, MD, PhD, Minoru Tanabe, MD, PhD, Zeniche Morise, MD, PhD, Horacio Asbun, MD, PhD, David Geller, MD, Mohammed Abu Hilal, MD, PhD, Mohamed Adam, MD, Adnan Alseidi, MD, EdM, International Hepatectomy Study Group, Alison Baskin, Annie Wong-On-Wing, Annie Yang, Devesh Sharma, Taisuke Imamura, Masanori Nakamura, Yuya Miura, Koki Hayashi, Masatsugu Ishii, Keita Shimata, Kazuya Hirukawa, Hiroki Ueda, June S. Peng, Lucas Thornblade, Kenzo Hirose, Kimberly Kirkwood, Eric Nakakura, Carlos Corvera, Ajay Maker

“…Textbook outcome is a composite measure that combines several favorable outcomes into a single metric and represents the optimal postoperative course. …”
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Production and Optimisation of Oxygenated Biofuel Blend Components via the Ethanolysis of Lignocellulosic Biomass: A Response Surface Methodology by Mohamad A. Nahil, Omar Aboelazayem, Scott Wiseman, Neel Herar, Valerie Dupont, Ali Alazzawi, Alison S. Tomlin, Andrew B. Ross

“…In this study, a response surface methodology (RSM) using a central composite design (CCD) was implemented to investigate the influence of process variables on ethyl levulinate (EL) production from the ethanolysis of waste corn cob samples, using sulphuric acid as a catalyst. …”
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Change in Dicrotic Notch Index Predicts Outcomes in Patients Undergoing Transcatheter Edge-to-Edge Repair for Mitral Regurgitation by Vishwum Kapadia, Shivabalan Kathavarayan Ramu, MD, Maryam Majeed-Saidan, MD, Rhonda Miyasaka, MD, Serge Harb, MD, Amar Krishnaswamy, MD

“…The cut point for change in DNI was determined and used to compare differences in composite clinical outcomes of mortality and heart failure hospitalization. …”
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Valorization of Andean berries through whole-fruit powder development by Manuela Gallón-Bedoya, Misael Cortés-Rodríguez, Jesús H Gil-González, José Luis Guil-Guerrero, Rodrigo Ortega-Toro

“…This research is aimed to evaluate the effect of the formulation and process of the Andean berries mix powder of cape gooseberry-strawberry-blackberry (BP) using SD technology. A central composite design was used, considering the following independent variables (IV): inlet air temperature (IAT) (140–160 °C), outlet air temperature (OAT) (80–90 °C), atomization disk speed (ADS) (20,000–24,000 rpm), and maltodextrin (MD) (6–10 %), and the dependent variables (DV): moisture (M), hygroscopicity (Hy), solubility (S), wettability (We), particle size (D[3,2]), bulk density (ρbulk), antioxidant capacity (ABTS and DPPH methods), total phenolic compounds (TP), vitamin C, and yield (Y). …”
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Machine learning and response surface methodology forecasting comparison for improved spray dry scrubber performance with brine sludge-derived sorbent by B.J. Chepkonga, L. Koech, R.S. Makomere, H.L. Rutto

“…The computational framework utilized experimental variables structured by CCD software as input metadata. …”
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A machine learning–based risk prediction model for atrial fibrillation in critically ill patients by Laith Alomari, MD, Yaman Jarrar, MD, Zaid Al-Fakhouri, MD, Emmanuel Otabor, MBBS, Justin Lam, MD, Jana Alomari

“…A compact model was developed using 15 variables and 2 novel features—one identifying patients 70 years of age or older with sepsis and another representing a composite score of pre-existing cardiac risk factors. …”
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The Establishment of a High-Moisture Corn Ear Model Based on the Discrete Element Method and the Calibration of Bonding Parameters by Chunrong Li, Zhounan Liu, Ligang Geng, Tianyue Xu, Weizhi Feng, Min Liu, Da Qiao, Yang Wang, Jingli Wang

“…Through calculations, this method enables the uniform arrangement of corn kernels on the cob, thereby accomplishing the establishment of a composite model for the high-moisture corn ear. The bonding parameters between the cob and kernels were determined through compression tests. …”
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Computed tomography based radiomics signature for predicting the expression of vascular endothelial growth factor in pediatric patients with nephroblastoma by Ma Fu, Han Qi, Suyue Zhu, Yan Gao, Yanlin Li, Jian Wu, Dongsheng Zhu

“…With the inclusion of a radiomics signature and clinical characteristics, a composite nomogram was created. Decision curve analysis (DCA) was used to evaluate the prediction performance. 5 carefully chosen radiomics features were used to create the radiomics signature. …”
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Effect of expansive agent on temperature and deformation of concrete under simulated actual construction condition by Ming Li, Ang Su, Hua Li, Yujiang Wang, Qian Tian

“…This paper aims to investigate the effect of calcium oxide EA (CEA), magnesium oxide EA (MEA), and calcium magnesium composite EA (CMA) on the temperature and deformation of concrete under simulated actual construction condition by concrete member test, and discusses the hydration heat, autogenous shrinkage deformation and mechanical properties of cement-based materials containing EA under standard laboratory condition. …”
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Design and Test of a Bionic Auxiliary Soil-Crushing Device for Strip-Tillage Machines by Kui Zhang, Yong-Ying Zhang, Xinliang Zhao, Yun Zhao, Xin Feng, Qi Wang, Jinwu Wang

“…A two-factor (working width and working depth), three-level central composite design (CCD) experiment was carried out using EDEM 2021 discrete element simulation software, taking the soil fragmentation rate and operational resistance as response variables. …”
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Visual function scale for identification of infants with low respiratory compliance by Eimei Harada, Masahiro Kinoshita, Sachiko Iwata, Mamoru Saikusa, Kennosuke Tsuda, Ryota Shindou, Takeshi Sahashi, Shin Kato, Yasumasa Yamada, Shinji Saitoh, Osuke Iwata

“…Results: The respiratory rate was identified as the primary independent variable for dynamic compliance in the univariate analysis. …”
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Time-dependent impact of immunosuppressant regimens on cardiovascular outcomes in kidney transplant recipients: a nationwide cohort study by Jinhyun Park, Wonhui Choi, Jinseub Hwang, Young-Mi Ah, Byung Ha Chung, Yun-Kyoung Song

“…Immunosuppressive medications were analyzed as time-dependent variables, and the primary outcome was MACEs, defined as a composite of myocardial infarction, coronary revascularization, ischemic stroke, and all-cause mortality.ResultsA total of 8,056 KTRs were included in the analysis, with significant risk factors for MACEs identified as male sex, older age, longer dialysis duration, lower economic status, and greater comorbidity. …”
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Association of the digital clock drawing test with amyloid and tau PET biomarkers in low age risk adults by Huitong Ding, Chenglin Lyu, Cody Karjadi, Preeti Sunderaraman, Christina B. Young, Elizabeth C. Mormino, Spencer Low, Sherral Devine, Katherine Gifford, Rhoda Au, Honghuang Lin

“…Notably, the combination of demographic variables and a composite dCDT score achieved a mean area under the receiver operating characteristics curve of 0.86 in detecting amyloid positivity. …”
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A Data Reconciliation-Based Method for Performance Estimation of Entrained-Flow Pulverized Coal Gasification by Yan Zhang, Kai Yue, Chang Yuan, Jiahao Xiang

“…By combining these models with thermodynamic equilibrium models, the modified R² of offline predicted syngas flow rate exceeds 0.92, and those of syngas compositions reach 0.72–0.85. Additionally, an Artificial Neural Network (ANN) model, trained on reconciled and predicted data, is proposed for real-time performance estimation. …”
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Optimization of micronizing zeolite grinding using artificial neural networks by Nikolić V., Trumić M., Tanikić D., Trumić M.S.

“…The aim of the experiment was to determine the optimal grinding conditions to obtain a powder with appropriate physico-chemical and microstructural characteristics that would find its potential application as a binder and ion exchanger in structural composites. The analysis of specific size classes of zeolite e after micronization was performed by grinding kinetics. …”
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AI-based prediction for the strength, cost, and sustainability of eggshell and date palm ash-blended concrete by Quanwei Zhao, Qi Chen, AlAteah Ali H., Alfares Abdulgafor M., Alinsaif Sadiq, Mostafa Sahar A.

“…Eggshell powder (ESP) and date palm ash (DPA) are increasingly used as sustainable cement substitutes in cementitious composites. This study used multi-expression programming (MEP) to develop prediction models due to its advantage of yielding model equations. …”
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