Promising clinical tools for specific Alzheimer disease diagnosis from plasma pTau217 and ApoE genotype in a cognitive disorder unit by Lourdes Álvarez-Sánchez, Carmen Peña-Bautista, Laura Ferré-González, Ángel Balaguer, Julián Luis Amengual, Miguel Baquero, Consuelo Cháfer-Pericás

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Optimization of Hydronic Heating System in a Commercial Building: Application of Predictive Control with Limited Data by Rana Loubani, Didier Defer, Ola Alhaj-Hasan, Julien Chamoin

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Population dynamics analysis of the interaction between tacrolimus and voriconazole in renal transplant recipients by Zhi-Hua Sun, Zhi-Hua Sun, Yi-Chang Zhao, Yi-Chang Zhao, Jia-Kai Li, Jia-Kai Li, Fenghua Peng, Feng Yu, Bi-Kui Zhang, Bi-Kui Zhang, Miao Yan, Miao Yan

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Multidisciplinary clinician perceptions on utility of a machine learning tool (ALERT) to predict 6‐month mortality and improve end‐of‐life outcomes for advanced cancer patients... by Nithya Krishnamurthy, Melanie Besculides, Ksenia Gorbenko, Melissa Mazor, Marsha Augustin, Jose Morillo, Marcos Vargas, Cardinale B. Smith

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Development and validation of a novel risk assessment model for accurate prediction of intraoperative hypothermia in adult patients undergoing different types of surgery: insights... by Bingbing Cao, Yongxing Li, Xiangnan Chen, Yong Liu, Yao Li, Haihua Shu, Qiang Wu, Fengtao Ji

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HBX Multi‐Mutations Combined With Traditional Screening Indicators to Establish a Nomogram Contributes to Precisely Stratify the High‐Risk Population of Hepatocellular Carcinoma... by Chao‐Jun Zhang, Xiao‐Mei Chen, Chang Yan, Rui‐Bo Lv, Sanchun An, Yun‐Xin Gao, Tian‐Ren Huang, Wei Deng

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An Adaptive Compound Control Strategy of Electric Vehicles for Coordinating Lateral Stability and Energy Efficiency by Xia Hua, Kai Xiang, Xiangle Cheng, Xiaobin Ning

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Development of a novel deep learning method that transforms tabular input variables into images for the prediction of SLD by Gabriel Cubillos, Javier Perez-Valenzuela, Herman Aguirre, Luz Martínez, Lorena Castro, Gabriel Mezzano, Claudio A. Perez

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A framework to predict zoonotic hosts under data uncertainty: A case study on betacoronaviruses by Andrea Tonelli, Marcus S. C. Blagrove, Maya Wardeh, Moreno Di Marco

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Predicting student self-efficacy in Muslim societies using machine learning algorithms by Mohammed Ba-Aoum, Mohammed Ba-Aoum, Mohammed Alrezq, Jyotishka Datta, Konstantinos P. Triantis

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Remaining Useful Life Prediction of Airplane Engine Based on Bidirectional Mamba and Causal Discovery by Min Li, Longxia Zhu, Meiling Luo, Ting Ke

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Comparative Performance Analysis of Optimization Algorithms in Artificial Neural Networks for Stock Price Prediction by Ekaprana Wijaya, Moch. Arief Soeleman, Pulung Nurtantio Andono

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Study on Flow Structure Characteristics Along the Latticework Duct Subchannels and Classification Boundary Prediction by Minlong Li, Huishe Wang, Ke Yang, Rongguo Yu, Jingze Ton

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An AI-Enabled Framework for <i>Cacopsylla chinensis</i> Monitoring and Population Dynamics Prediction by Ruijun Jing, Deyan Peng, Jingtong Xu, Zhengjie Zhao, Xinyi Yang, Yihai Yu, Liu Yang, Ruiyan Ma, Zhiguo Zhao

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Computational study and prediction of infection risk probability of respiratory diseases inside a classroom by Oskar Urbina-Garcia, Iñigo Aramendia, Carolina Marugán-Cruz, Wilfried Coenen, Sergio Sánchez-Delgado, Unai Fernandez-Gamiz, Ekaitz Zulueta

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Optimizing prediction of metastasis among colorectal cancer patients using machine learning technology by Raoof Nopour

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Nutrient Content Prediction and Geographical Origin Identification of Bananas by Combining Hyperspectral Imaging with Chemometrics by Honghui Xiao, Chunlin Li, Mingyue Wang, Zhibo Huan, Hanyi Mei, Jing Nie, Karyne M. Rogers, Zhen Wu, Yuwei Yuan

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Expert-augmented machine learning for predicting extubation readiness in the pediatric intensive care unit by Jean Digitale, Deborah Franzon, Jin Ge, Charles McCulloch, Mark J. Pletcher, Efstathios D. Gennatas

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Comparative Analysis of Data Visualization and Deep Learning Models in Air Quality Forecasting by Bihter Daş, Damla Mengus

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Development and validation of an explainable machine learning model for predicting osteoporosis in patients with type 2 diabetes mellitus by Qipeng Wei, Zihao Liu, Xiaofeng Chen, Hao Li, Weijun Guo, Qingyan Huang, Jinxiang Zhan, Shiji Chen, Dongling Cai, Dongling Cai

“…Eight supervised ML algorithms were applied to construct predictive models. Model performance was evaluated based on the area under the receiver operating characteristic curve (AUC), calibration plots, decision curve analysis (DCA), accuracy, sensitivity, specificity, and F1 score. …”
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