Integrating Motivation Theory into the AIED Curriculum for Technical Education: Examining the Impact on Learning Outcomes and the Moderating Role of Computer Self-Efficacy by Shao-Hsun Chang, Kai-Chao Yao, Yao-Ting Chen, Cheng-Yang Chung, Wei-Lun Huang, Wei-Sho Ho

“…The integration of artificial intelligence (AI) technologies into education has gained increasing attention, yet limited research examines how the curriculum design can enhance learning outcomes and influence learners’ intentions to continue AI learning. …”
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Predicting cardiovascular disease and all-cause mortality using the lymphocyte-to-monocyte ratio: Insights from explainable machine learning models by Jichao Wu, Die Huang, Jiefang Li, Jingxing Yi, Yu Lei, Jun Yin

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Peningkatan hasil belajar matematika materi menggunakan pecahan dalam pemecahan masalah dengan pendekatan Contextual Teaching Learning (CTL) by Asrial Asrial

“…Learning mathematics using fractions in problem-solving is boring for students. …”
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Mapping groundwater potential zone by robust machine learning algorithms & remote sensing techniques in agriculture dominated area, Bangladesh by M. M. Shah Porun Rana, Muhammad Tauhidur Rahman, Md Fuad Hassan

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The evolutionary journey to a new normal for learning and capacity building of healthcare workers to prepare and respond to health emergencies across Africa by Boukaré Bonkoungou, Fausta Mosha, Amarachi Abianuru, Joseph Okeibunor, Heini Utunen, Giselle Balaciano, Ana C. Barbosa de Lima, Lauren Burke, Shannon McKenna, Sukriti Nag, Abdou Salam Gueye, Bruce Struminger

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Predictive model for abdominal liposuction volume in patients with obesity using machine learning in a longitudinal multi-center study in Korea by Hyunji Sang, Jaeyu Park, Soeun Kim, Myeongcheol Lee, Hojae Lee, Sun-Ho Lee, Dong Keon Yon, Sang Youl Rhee

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Advancing privacy-aware machine learning on sensitive data via edge-based continual µ-training for personalized large models by Zhaojing Huang, Leping Yu, Luis Fernando Herbozo Contreras, Kamran Eshraghian, Nhan Duy Truong, Armin Nikpour, Omid Kavehei

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Implementation of the project-based learning (PjBL) model in sharpening students' critical thinking as an effort to strengthen the profile of Pancasila students by Alfi Nur Hidayati, Akhtim Wahyuni

“…So that learners get better information from their learning experience.…”
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Learning to Shape Transformation – How Individual Schools can be Supported in Implementing a Newly Developed ESD Curriculum with Training Concept by Lindau-Bank Detlev, Stein Margit

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Author Correction: Layer-by-layer phase transformation in Ti3O5 revealed by machine-learning molecular dynamics simulations by Mingfeng Liu, Jiantao Wang, Junwei Hu, Peitao Liu, Haiyang Niu, Xuexi Yan, Jiangxu Li, Haile Yan, Bo Yang, Yan Sun, Chunlin Chen, Georg Kresse, Liang Zuo, Xing-Qiu Chen

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Upper Extremity Motor Learning among Individuals with Parkinson's Disease: A Meta-Analysis Evaluating Movement Time in Simple Tasks by K. Felix, K. Gain, E. Paiva, K. Whitney, M. E. Jenkins, S. J. Spaulding

“…Motor learning has been found to occur in the rehabilitation of individuals with Parkinson's disease (PD). …”
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Learnings from Rolls‐Royce hybrid propulsion systems in flight testing of High Power, High Scalability Hybrid Powertrain aircraft by Péter Bodolai, Attila Vörösváczki, Gábor Bihari, Szabolcs Fási, Péter Szabó, Zoltán Koltai

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Crack Identification Method of Steel Fiber Reinforced Concrete Based on Deep Learning: A Comparative Study and Shared Crack Database by Yang Ding, Shuang-Xi Zhou, Hai-Qiang Yuan, Yuan Pan, Jing-Liang Dong, Zhong-Ping Wang, Tong-Lin Yang, An-Ming She

“…Furthermore, the crack database is expanded by the migration learning method and the crack database is shared on the Baidu online disk. …”
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Machine Learning-Based Alzheimer’s Disease Stage Diagnosis Utilizing Blood Gene Expression and Clinical Data: A Comparative Investigation by Manash Sarma, Subarna Chatterjee

“…Both of these samples, obtained from participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI), were independently analyzed utilizing machine learning (ML)-based multiclassifiers. This study applied novel machine learning-based data augmentation techniques to gene expression profile data that are high-dimensional, low-sample-size (HDLSS) and inherently highly imbalanced. …”
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Development and routine implementation of deep learning algorithm for automatic brain metastases segmentation on MRI for RANO-BM criteria follow-up by Loïse Dessoude, Raphaëlle Lemaire, Romain Andres, Thomas Leleu, Alexandre G. Leclercq, Alexis Desmonts, Typhaine Corroller, Amirath Fara Orou-Guidou, Luca Laduree, Loic Le Henaff, Joëlle Lacroix, Alexis Lechervy, Dinu Stefan, Aurélien Corroyer-Dulmont

Subjects: “…Deep learning…”
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Deep Learning in Oral Hygiene: Automated Dental Plaque Detection via YOLO Frameworks and Quantification Using the O’Leary Index by Alfonso Ramírez-Pedraza, Sebastián Salazar-Colores, Crystel Cardenas-Valle, Juan Terven, José-Joel González-Barbosa, Francisco-Javier Ornelas-Rodriguez, Juan-Bautista Hurtado-Ramos, Raymundo Ramirez-Pedraza, Diana-Margarita Córdova-Esparza, Julio-Alejandro Romero-González

Subjects: “…deep learning…”
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Modeling dose uncertainty in cone-beam computed tomography: Predictive approach for deep learning-based synthetic computed tomography generation by Cédric Hémon, Lucía Cubero, Valentin Boussot, Romane-Alize Martin, Blanche Texier, Joël Castelli, Renaud de Crevoisier, Anaïs Barateau, Caroline Lafond, Jean-Claude Nunes

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Perilaku belajar dan self regulated learning siswa selama belajar dari rumah pada masa pandemi Covid-19 by Adi Atmoko, Khairul Bariyyah, Augusto Da Costa, Husni Hanafi, Eny Tri Wahyuni

“…This study aims to (1) describe student learning behavior and student self-regulated learning while studying from home, (2) analyze the relationship between self-regulated learning and student learning behavior while studying from home. …”
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Development of E-Module "Community Needs Analysis" Based on Massive Open Online Course (MOOC) : Learning Innovation for Community Practitioners by Rakhmaditya Dwi Noorrizki, Alfina Nur Azri, Anjarie Dharmastuti, Ikhwanul Ihsan Armalid

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Identification and Validation of a Novel Immune Infiltration-Based Diagnostic Score for Early Detection of Hepatocellular Carcinoma by Machine-Learning Strategies by Xuli Guo, Hailin Xiong, Shaoting Dong, Xiaobing Wei

“…After batch effect removal, differentially expressed genes (DEGs) were conducted between 209 HCC and 146 control tissues and functional correlation analyses were performed. Two machine learning algorithms were used to develop diagnostic signatures. …”
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