ARTIFICIAL LEARNING BASED ON KERNEL SVM FOR THE PREDICTION OF CARDIOVASCULAR DISEASE HYPERTENSION by Patient MUSUBAO SWAMBI, Albert Ntumba Nkongolo, Pierre Kafunda Katalay, Rostin Mabela Matendo Makengo, Eugène Mbuyi Mukendi

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Virtual undergraduate chemical engineering labs based on density functional theory calculations by Altarawneh Mohammednoor

“…We hope that DFT-operated virtual labs will assist students in attaining learning outcomes and promote their self-learning in the above-mentioned subjects. …”
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Composite Bayesian Optimization in function spaces using NEON—Neural Epistemic Operator Networks by Leonardo Ferreira Guilhoto, Paris Perdikaris

“…Abstract Operator learning is a rising field of scientific computing where inputs or outputs of a machine learning model are functions defined in infinite-dimensional spaces. …”
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The Impact of Noise on Learning in Children and Adolescents: A Meta-Analysis by Gabriela Fretes, Ramon Palau

“…Different noise types were analyzed in relation to cognitive functions such as attention, memory, comprehension, and overall academic performance. …”
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Leadership for Student Participation in Data-Use Professional Learning Communities by Hilde Forfang, Cindy Louise Poortman, Mette Marit Jenssen, Kim Schildkamp

Subjects: “…leadership core functions…”
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Characterization of Neural Interaction During Learning and Adaptation from Spike-Train Data by Liqiang Zhu, Ying-Cheng Lai, Frank C. Hoppensteadt, Jiping He

Subjects: “…neural learning…”
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The changes in brain network functional gradients and dynamic functional connectivity in SeLECTS patients revealing disruptive and compensatory mechanisms in brain networks by Linfeng Song, Guangrong Wu, Jiaren Zhang, Benqing Liu, Xu Chen, Junjun Wang, Xiaoyu Gu, Binlin Tian, Yongzhe Li, Anjie Zhang, Xuejin Ma, Lin Jiang

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AI-Driven Integration of Deep Learning With Lung Imaging, Functional Analysis, and Blood Gas Metrics for Perioperative Hypoxemia Prediction by Kecheng Huang, Chujun Wu, Rongpeng Pi, Jieyu Fang

“… This viewpoint article explores the transformative role of artificial intelligence (AI) in predicting perioperative hypoxemia through the integration of deep learning with multimodal clinical data, including lung imaging, pulmonary function tests, and arterial blood gas (ABG) analysis. …”
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Protocol to analyze deep-learning-predicted functional scores for noncoding de novo variants and their correlation with complex brain traits by Enrique Mondragon-Estrada, Sarah U. Morton

“…Here, we present a protocol for prioritizing variants by generating deep-learning-predicted functional scores and relating them with brain traits. …”
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Study of Cathode Materials for Na-Ion Batteries: Comparison Between Machine Learning Predictions and Density Functional Theory Calculations by Claudio Ronchetti, Sara Marchio, Francesco Buonocore, Simone Giusepponi, Sergio Ferlito, Massimo Celino

“…We trained crystal graph convolutional neural networks and geometric crystal graph neural networks, and we demonstrate the ability of the machine learning algorithms to predict the formation energy of the candidate materials as calculated by the density functional theory. …”
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SUBSTANTIAL VERSUS FUNCTIONAL PRINCIPAL AND THEIR INFLUENCE ON THE SUCCESS OF THE IMPLEMENTATION PROCESS OF ALTERNATIVE LEARNING TEACHING AND ASSESSMENT IN HIGH SCHOOLS IN ISRAEL by Sofy AMNONY

“…The article deals with two main types of school principals, a substantial principal and a functional principal, which were discovered during research, conveying the influence of principals’ different management styles on alternative learning, teaching and assessment processes in high schools in Israel. …”
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Exploring the biological function of dreaming: lessons learned from recruitment challenges in a pilot study with PCA stroke patients by Tamara Fischmann, Luisa Peters, Vanessa Rieker, Michael Koslowski

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Machine learning prediction model for functional prognosis of acute ischemic stroke based on MRI radiomics of white matter hyperintensities by Yayuan Xia, Linhui Li, Peipei Liu, Tianxu Zhai, Yibing Shi

“…Conclusion The FLAIR sequence-based WMH radiomics approach demonstrates effective prediction of the 90-day functional prognosis in patients with AIS. The integration of TWMH radiomics and clinical factors in a combined model exhibits superior performance. …”
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Fast decliner phenotype of chronic obstructive pulmonary disease (COPD): applying machine learning for predicting lung function loss by David B Price, Vasilis Nikolaou, Sebastiano Massaro, Wolfgang Garn, Masoud Fakhimi, Lampros Stergioulas

“…We characterised patients with the ‘fast decliner’ phenotype, determined its reproducibility and predicted lung function decline after COPD diagnosis.Methods A prospective 4 years observational study that applies machine learning tools to identify COPD phenotypes among 13 260 patients from the UK Royal College of General Practitioners and Surveillance Centre database. …”
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Rapid Design of Efficient Mn3O4‐Based Photocatalysts by Machine Learning and Density Functional Theory Calculations by Haoxin Mai, Xuying Li, Tu C. Le, Salvy P. Russo, David A. Winkler, Dehong Chen, Rachel A. Caruso

Subjects: “…density functional theory calculations…”
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Interpretations of Pre-service Elementary Mathematics Teachers on the Functions of Non-Textual Elements: Case Study on Algebra Learning Area by Murat Genç, Mustafa Akıncı

“…Pre-service teachers were found to have diverse but sometimes overlapping interpretations of the functions of each non-textual element. However, the functional diversity of non-textual elements may have differentiated their interpretations, as visual literacy skills and strategies are required to interpret the intended use of non-textual elements. …”
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A Case Study on SAL-Based Teaching and Learning in a Functional Clothing and Materials Course Using Generative AI by Hyun Ah Kim

“…This study explores the application of Smart Action Learning (SAL) and generative AI tools in the “Functional Clothing and Materials” course to enhance student engagement, problem-solving abilities, and practical skill acquisition. …”
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MRI-Based Machine Learning and Radiomics Methods for Assessing Spinal Cord Function in Patients with Mild Cervical Spondylotic Myelopathy by He Wang, Kai Wang, Yutian Wang, Zhenlei Liu, Lei Zhang, Shanhang Jia, Kun He, Xiangyu Zhang, Hao Wu

“…While PET evaluates spinal cord function, its cost and radiation limit its use. (2) Methods: In this prospective study, patients with mild cervical spondylosis underwent preoperative 18F-FDG PET-MRI. …”
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Functional Disability and Psychological Impact in Headache Patients: A Comparative Study Using Conventional Statistics and Machine Learning Analysis by Jong-Ho Kim, Hye-Sook Kim, Jong-Hee Sohn, Sung-Mi Hwang, Jae-Jun Lee, Young-Suk Kwon

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Disulfidptosis-related gene in acute myocardial infarction and its diagnostic value and functions based on bioinformatics analysis and machine learning by Liwen Chen, Jinru Wei, Jinru Wei, Guoxiong Deng, Guoxiong Deng, Guien Xu

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