Estimating the Risk of Lower Extremity Complications in Adults Newly Diagnosed With Diabetic Polyneuropathy: Retrospective Cohort Study by Alyce S Adams, Catherine Lee, Gabriel Escobar, Elizabeth A Bayliss, Brian Callaghan, Michael Horberg, Julie A Schmittdiel, Connie Trinacty, Lisa K Gilliam, Eileen Kim, Nima S Hejazi, Lin Ma, Romain Neugebauer

“…ObjectiveThis study aimed to develop an electronic medical record–based machine learning algorithm that would predict lower extremity complications. …”
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Combined mechanistic and machine learning method for construction of oil reservoir permeability map consistent with well test measurements by Evgenii Kanin, Alsu Garipova, Sergei Boronin, Vladimir Vanovskiy, Albert Vainshtein, Andrey Afanasyev, Andrei Osiptsov, Evgeny Burnaev

“…This inverse optimization problem is addressed by repeatedly solving forward problems, where an artificial neural network (ANN) predicts the integral permeability of the formation surrounding a well and skin factor. …”
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Identification and validation of endoplasmic reticulum autophagy-related potential biomarkers in periodontitis by Ruyue Wang, Jinyue Hu, Qing Sun, Shuixiang Guo, Gege Zhang, Ao Lu, Shuo Liu, Xue Yang, Lina Wang

“…Clinical samples examined by RT-qPCR verified that these ER-phagy-related signature genes in periodontitis may better predict the development of periodontitis.ER-phagy is closely related to the pathological process of periodontitis. …”
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Physics-informed modeling of splitting tensile strength of recycled aggregate concrete using advanced machine learning by Kennedy C. Onyelowe, Viroon Kamchoom, Shadi Hanandeh, S. Anandha Kumar, Rolando Fabián Zabala Vizuete, Rodney Orlando Santillán Murillo, Susana Monserrat Zurita Polo, Rolando Marcel Torres Castillo, Ahmed M. Ebid, Paul Awoyera, Krishna Prakash Arunachalam

“…Five advanced machine learning techniques created using the “Weka Data Mining” software version 3.8.6 were applied to predict the Fsp and the Hoffman & Gardener method and performance metrics were also used to evaluate the sensitivity and performance of the variables and ML models, respectively. …”
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microRNA-183–5p induces cell density-dependent apoptosis through the regulation of Presenilin 2 by Yuki Yabuuchi, Yosuke Matsuno, Kai Yazaki, Wei Zhen Ting, Kengo Nishino, Sosuke Matsumura, Kenya Kuramoto, Kazufumi Yoshida, Masashi Matsuyama, Takumi Kiwamoto, Yuko Morishima, Nobuyuki Hizawa

“…PSEN2 regulated the development of apoptosis, which is accompanied by increased Bcl-2 expression, decreased Bax expression, and activated PI3K/Akt pathway. PSEN2 is predicted to be targeted by microRNA-183–5p (miR-183–5p) by several algorithms. …”
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Spatio-Temporal Habitat Dynamics of Migratory Small Yellow Croaker (<i>Larimichthys polyactis</i>) in Hangzhou Bay, China by Xiangyu Long, Dong Wang, Pengbo Song, Mengwen Han, Rijin Jiang, Yongdong Zhou

“…We evaluated the performance of eleven modeling algorithms to identify the most accurate model for predicting small yellow croaker distributions. …”
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Critical load exceedances for North America and Europe using an ensemble of models and an investigation of causes of environmental impact estimate variability: an AQMEII4 study by P. A. Makar, P. Cheung, C. Hogrefe, A. Akingunola, U. Alyuz, J. O. Bash, M. D. Bell, R. Bellasio, R. Bianconi, T. Butler, H. Cathcart, O. E. Clifton, O. E. Clifton, A. Hodzic, I. Kioutsioukis, R. Kranenburg, A. Lupascu, A. Lupascu, J. A. Lynch, K. Momoh, J. L. Perez-Camanyo, J. Pleim, Y.-H. Ryu, R. San Jose, D. Schwede, D. Schwede, T. Scheuschner, M. W. Shephard, R. S. Sokhi, S. Galmarini

“…If model–measurement fusion is only applied to some but not all of the fields contributing to the total deposition of sulfur or nitrogen, the corrections may result in greater variability between models or less accurate results for an ensemble of models, for those cases where an unobserved or unused observed component contributes significantly to predicted total deposition.</p> <p>Based on these results, an increased process-research focus is therefore recommended for the following model processes and for observations which may assist in model evaluation and improvement: multiphase hydrometeor scavenging combined with updated particle dry-deposition, cuticle, and soil deposition pathway algorithms for acidifying gases, base cation chemistry and emissions, and NH<span class="inline-formula">₃</span> bidirectional fluxes. …”
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Applied AMT machine learning and multi-objective optimization for enhanced performance and reduced environmental impact of sunflower oil biodiesel in compression ignition engine by Ali A. Al-jabiri, Hyder H. Balla, Mudhaffar S. Al-zuhairy, Hussein Alahmer, Ahmed Al-Manea, Raed Al-Rbaihat, Ali Alahmer

“…The AMT models demonstrate high prediction accuracy, with coefficient of determination (R2) values exceeding 0.98.…”
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A novel data-driven based high-precision building roof contour full-automatic extraction and structured 3D reconstruction method combining stereo images and LiDAR points by Xiongwu Xiao, Kai Wang, Zhichao Zhong, Wenhu Qu, Weiwei Wu, Zhigao Cui, Yanzhao Su, Aihua Li, Jianya Gong, Deren Li

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Quantifying the chemical composition of weathering products of Hainan basalts with reflectance spectroscopy and its implications for Mars by Xing Wu, JiaCheng Liu, WeiChao Sun, Yang Liu, Joseph Michalski, Wei Tan, XiaoRong Qin, YongLiao Zou

“…We established a quantitative spectral model by combining the genetic algorithm and partial least squares regression (GA-PLSR) to predict the chemical properties (SiO2, Al2O3, Fe2O3) and index of laterization (IOL). …”
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Neural correlates of device-based sleep characteristics in adolescents by Qing Ma, Barbara J. Sahakian, Bei Zhang, Zeyu Li, Jin-Tai Yu, Fei Li, Jianfeng Feng, Wei Cheng

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NETosis-based prognostic model reveals immune modulation in clear cell renal cell carcinoma using single-cell and bulk RNA sequencing by Zijie Yu, Zihao Xu, Xi Zhang, Wenchuan Shao, Da Zhong, Xinghan Yan, Tingfei Jiang, Yichun Wang, Ninghong Song

“…Netosis and TME scores exhibited a high degree of predictive power for patient survival, as illustrated by Kaplan-Meier (KM) curves. …”
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Differences in Characteristics of Peripartum Patients Who Did and Did Not Require an Upgrade to the Intensive Care Unit: A Propensity Score Matching Study by Jennifer A. Walker, Jerry M. Yang, Saad Pirzada, Manahel Zahid, Samantha Asuncion, Amanda Tuchler, Gillian Cooper, Allison Lankford, Emad Elsamadicy, Quincy K. Tran

“…The Sequential Organ Failure Assessment score at Maternal Fetal Ward admission was most predictive, followed by the Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and lactate dehydrogenase levels. …”
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Human-Annotated Label Noise and Their Impact on ConvNets for Remote Sensing Image Scene Classification by Longkang Peng, Tao Wei, Xuehong Chen, Xiaobei Chen, Rui Sun, Luoma Wan, Jin Chen, Xiaolin Zhu

“…Additionally, the label noise estimation algorithm (confident learning) cannot fully identify label noise. …”
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Evaluating Material Parameter Influence on Drapability Using VStitcher by Malin Schiller, Soraya Flohr, Jeanne Marisol Delmas, Anja Krüger, Anne-Marie Miene, Patrizia Zimmermann, Lena Wolf, Miriam Seffers, Michelle-Sophie Ruchay-Drammeh, Ulrike Reinhardt, Lilia Sabantina

“…It is a matter not only of generating photo-realistic images in 3D garment simulations, but also of making reliable predictions about the physical behavior of textile materials in order to achieve realistic outcomes. …”
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Rapid identification and phenotyping of nonalcoholic fatty liver disease patients using a machine‐based approach in diverse healthcare systems by Anna O. Basile, Anurag Verma, Leigh Anne Tang, Marina Serper, Andrew Scanga, Ava Farrell, Brittney Destin, Rotonya M. Carr, Anuli Anyanwu‐Ofili, Gunaretnam Rajagopal, Abraham Krikhely, Marc Bessler, Muredach P. Reilly, Marylyn D. Ritchie, Nicholas P. Tatonetti, Julia Wattacheril

“…Clinical chart review identified a high positive predictive value (PPV) across all healthcare systems: 91% at CUIMC, 75% at UPHS, and 85% at VUMC, and a sensitivity of 79.6%. …”
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Forecasting Urban Sprawl Dynamics in Islamabad: A Neural Network Approach by Saddam Sarwar, Hafiz Usman Ahmed Khan, Falin Wu, Sarah Hasan, Muhammad Zohaib, Mahzabin Abbasi, Tianyang Hu

“…Utilizing a land change modeler (LCM), forecasts of the future conditions in 2025, 2030, and 2035 are predicted. The artificial neural network (ANN) model embedded in IDRISI software 18.0v based on a well-defined backpropagation (BP) algorithm was used to simulate future urban sprawl considering the historical pattern for 2015–2020. …”
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A Coupled Least Absolute Shrinkage and Selection Operator–Backpropagation Model for Estimating Evapotranspiration in Xizang Plateau Irrigation Districts with Reduced Meteorological... by Qiang Meng, Jingxia Liu, Fengrui Li, Peng Chen, Junzeng Xu, Yawei Li, Tangzhe Nie, Yu Han

“…Short-term ET_O predictions for the three districts were also conducted using the mean-generating function optimal subset regression algorithm. …”
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Assessment of the Maize Crop Water Stress Index (CWSI) Using Drone-Acquired Data Across Different Phenological Stages by Mpho Kapari, Mbulisi Sibanda, James Magidi, Tafadzwanashe Mabhaudhi, Sylvester Mpandeli, Luxon Nhamo

“…This study sought to predict a foliar temperature-derived maize CWSI as a proxy for crop water stress using UAV-acquired spectral variables together with random forest regression throughout the vegetative and reproductive growth stages. …”
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Relationship of transforming growth factor β1 with diabetic retinopathy in type 2 diabetes by A.S. Hudz, V.A. Serhiyenko, I.V. Kudryl, V.G. Guryanov, M.I. Kovtun, S.V. Ziablitsev

“…A three-factor classification model was created on the identified features, which included a system of equations that predicted PDR with 100% accuracy. The overall prediction accuracy of the model was 88.2 % (95% CI 80.4–93.8 %). …”
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