Utilization of Machine Learning for Predicting Corrosion Inhibition by Quinoxaline Compounds by Muhamad Fadil, Muhamad Akrom, Wise Herowati

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Statistical and machine learning analysis of diesel engines fueled with Moringa oleifera biodiesel doped with 1-hexanol and Zr2O3 nanoparticles by K. Sunil Kumar, Abdul Razak, M. K. Ramis, Shaik Mohammad Irshad, Saiful Islam, Anteneh Wogasso Wodajo

Subjects: “…Machine learning…”
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Machine Learning Forecasting of Commercial Buildings’ Energy Consumption Using Euclidian Distance Matrices by Connor Scott, Alhussein Albarbar

Subjects: “…machine learning…”
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Predicting Crime Time Intervals Using Machine Learning Models by Arief Deswandi, Widi Hastomo

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Clustering‐based risk stratification of prediabetes populations: Insights from the Taiwan and UK Biobanks by Djeane Debora Onthoni, Ying‐Erh Chen, Yi‐Hsuan Lai, Guo‐Hung Li, Yong‐Sheng Zhuang, Hong‐Ming Lin, Yu‐Ping Hsiao, Ade Indra Onthoni, Hung‐Yi Chiou, Ren‐Hua Chung

Subjects: “…Machine learning…”
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Exploring associations among pro-inflammatory cytokines, osteoarthritis, and gut microbiome composition in individuals with obesity using machine learning by Cameron Kurz, Liubov Arbeeva, M. Andrea Azcarate-Peril, Delisha A. Stewart, B. Duncan X. Lascelles, Richard F. Loeser, Amanda E. Nelson

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Nonlinear Calibration Method for FMG Line-of-Sight Magnetic Field by Ziyao Hu, Kaifan Ji, Xianyong Bai, Yuanyong Deng, Jiangtao Su, Jingjing Guo, Suo Liu, Xiao Yang

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Validation of Quantitative Ultrasound and Texture Derivative Analyses-Based Model for Upfront Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer by Adrian Wai Chan, Lakshmanan Sannachi, Daniel Moore-Palhares, Archya Dasgupta, Sonal Gandhi, Rossanna Pezo, Andrea Eisen, Ellen Warner, Frances C. Wright, Nicole Look Hong, Ali Sadeghi-Naini, Mia Skarpathiotakis, Belinda Curpen, Carrie Betel, Michael C. Kolios, Maureen Trudeau, Gregory J. Czarnota

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Machine learning model for predicting corneal stiffness and identifying keratoconus based on ocular structures by Longhui Li, Yifan Xiang, Xi Chen, Duoru Lin, Lanqin Zhao, Jun Xiao, Zhenzhe Lin, Jianyu Pang, Xiaotong Han, Lixue Liu, Yuxuan Wu, Zhenzhen Liu, Jingjing Chen, Jing Zhuang, Keming Yu, Haotian Lin

Subjects: “…Machine learning…”
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Supervised machine learning for microbiomics: Bridging the gap between current and best practices by Natasha Katherine Dudek, Mariami Chakhvadze, Saba Kobakhidze, Omar Kantidze, Yuriy Gankin

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Defect modeling in semiconductors: the role of first principles simulations and machine learning by Md Habibur Rahman, Arun Mannodi-Kanakkithodi

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Rosette Trajectory MRI Reconstruction with Vision Transformers by Muhammed Fikret Yalcinbas, Cengizhan Ozturk, Onur Ozyurt, Uzay E. Emir, Ulas Bagci

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Estimating the effect of hitting strategies in baseball using counterfactual virtual simulation with deep learning by Nakahara Hiroshi, Takeda Kazuya, Fujii Keisuke

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Development of a prediction model for chemotherapy and immunotherapy response in esophageal squamous cell carcinoma patients using machine learning algorithms by CHEN Jincheng, ZHANG Xiaoqin, LIU Jie

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Gaze Tracking in Semi-Autonomous Grasping by Claudio Castellini

Subjects: “…machine learning…”
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Early detection of bloodstream infection in critically ill children using artificial intelligence by Hye-Ji Han, Kyunghoon Kim, June Dong Park

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Blood predictive biomarkers for cognitive impairment among community-dwelling older adults: a cross-sectional study in China by Bosi Dong, Mengqiao He, Shuming Ji, Wenjie Yang, Qiulei Hong, Yusha Tang, Anjiao Peng, Lei Chen

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A predictive framework using advanced machine learning approaches for measuring and analyzing the impact of synthetic agrochemicals on human health by Sahezpreet Singh, Puneet Kaur, Inderdeep Kaur, Gurpreet Singh, Satinder Kaur, Parminder Kaur

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A multivariate analysis of the early dropout using classical machine learning and local interpretable model-agnostic explanations by Thanh Hai Nguyen, Phuong Le, Tuyen Thanh Thi Nguyen, Anh Kim Su

Subjects: “…Dropout Prediction, Machine learning, Explanation…”
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Machine Learning in Acute Stroke Neuroimaging. A Systematic Literature Review by D. Matuliauskas, I. Stražnickaitė, A. Samuilis, D. Jatužis

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