Application of Deep Learning to the Classification of Stokes Profiles: From the Quiet Sun to Sunspots by Ryan J. Campbell, M. Mathioudakis, Carlos Quintero Noda, P. H. Keys, D. Orozco Suárez

“…Previous studies used manual methods or unsupervised machine learning (ML) to classify the shapes of circular polarization profiles. …”
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Automatic detection of floating instream large wood in videos using deep learning by J. Aarnink, J. Aarnink, T. Beucler, T. Beucler, M. Vuaridel, V. Ruiz-Villanueva, V. Ruiz-Villanueva

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Construction and validation of immune prognosis model for lung adenocarcinoma based on machine learning by Jinyu Zheng, Xiaoyi Xu, Xianguo Chen, Xianshuai Li, Miao Fu, Yiping Zheng, Jie Yang

“…Protein expression and biological functions of hub genes were validated using the HPA database and GSEA.ResultsA total of 1,822 DEGs were identified, with 68 immune-related genes significantly associated with LUAD prognosis. …”
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Blockchain framework with IoT device using federated learning for sustainable healthcare systems by B. Bhasker, P. Muralidhara Rao, P. Saraswathi, S. Gopal Krishna Patro, Javed Khan Bhutto, Saiful Islam, Mohammed Kareemullah, Addisu Frinjo Emma

“…Abstract The Internet of Medical Things (IoMT) sector has advanced rapidly in recent years, and security and privacy are essential considerations in the IoMT due to the extensive scope and implementation of IoMT networks. Machine learning (ML) and blockchain (BC) technologies have dramatically improved the functionalities and services of Healthcare 5.0, giving rise to a new domain termed Smart Healthcare. …”
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Quantifying training response in cycling based on cardiovascular drift using machine learning by Artur Barsumyan, Artur Barsumyan, Raman Shyla, Anton Saukkonen, Christian Soost, Jan Adriaan Graw, Rene Burchard, Rene Burchard, Rene Burchard

“…In the new era of technology, we propose an experimental method using machine learning (ML) to measure response quantified as aerobic fitness level based on cardiovascular drift and aerobic decoupling data.MethodsTwenty well-trained athletes in cycling-based sports performed monthly aerobic fitness tests over five months, riding at 75% of their functional threshold power for 60 min. …”
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Challenges and Strategies of Remote Foreign Language Learning for Students with Autism Spectrum Disorder by Iryna Haidai, Liudmyla Suvorova, Nataliia Pankovyk, Yuliia Herasymchuk, Olha Zadoienko

“…People with cognitive impairments constantly face a number of modern challenges, including a pandemic, martial law, and instability of psychoemotional functions, which already complicates the education of students with autism. …”
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Identification of signature genes and subtypes for heart failure diagnosis based on machine learning by Yanlong Zhang, Yanming Fan, Fei Cheng, Dan Chen, Hualong Zhang

“…Consequently, identifying specific genes for HF at the transcriptomic level may enhance early detection and allow for more targeted therapies for these individuals.MethodsHF datasets were acquired from the Gene Expression Omnibus (GEO) database (GSE57338), and through the application of bioinformatics and machine-learning algorithms. We identified four candidate genes (FCN3, MNS1, SMOC2, and FREM1) that may serve as potential diagnostics for HF. …”
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Machine learning reveals the dynamic importance of accessory sequences for Salmonella outbreak clustering by Chao Chun Liu, William W. L. Hsiao

“…Annotating the genomic features important for cluster classification revealed functional enrichment of molecular fingerprints in genes involved in membrane transportation, trafficking, and carbohydrate metabolism. …”
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Deep-Learning-Based Land Cover Mapping in Franciacorta Wine Growing Area by Girma Tariku, Isabella Ghiglieno, Andres Sanchez Morchio, Luca Facciano, Celine Birolleau, Anna Simonetto, Ivan Serina, Gianni Gilioli

“…Land cover mapping is essential to understanding global land-use patterns and studying biodiversity composition and the functioning of eco-systems. The introduction of remote sensing technologies and artificial intelligence models made it possible to base land cover mapping on satellite imagery in order to monitor changes, assess ecosystem health, support conservation efforts, and reduce monitoring time. …”
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The organization of interaction of subjects of educational process when using platforms of distance learning by F. S. Mukhametzyanova, A. R. Kamaleeva, S. Yu. Gruzkova, R. R. Hadiullina

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Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction by Jingjing Chen, Dan Zhang, Chengxiu Zhu, Lin Lin, Kejun Ye, Ying Hua, Mengjia Peng

“…A multi-algorithm machine learning framework was employed to optimize predictive performance, with model interpretability achieved through SHapley Additive exPlanations and diagnostic accuracy validated by receiver operating characteristic curves. …”
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Stacked Ensemble Learning for Classification of Parkinson’s Disease Using Telemonitoring Vocal Features by Bolaji A. Omodunbi, David B. Olawade, Omosigho F. Awe, Afeez A. Soladoye, Nicholas Aderinto, Saak V. Ovsepian, Stergios Boussios

“…<b>Background:</b> Parkinson’s disease (PD) is a progressive neurodegenerative condition that impairs motor and non-motor functions. Early and accurate diagnosis is critical for effective management and care. …”
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A machine learning-based risk prediction model for diabetic oral ulceration by Wang Xiaoling, Wang BingQian, Zhu Zhenqi, Li Wen, Gu Shuyan, Chen Hanbei, Xin Feng, Chenglong Yang, Jutang li, Guoyao Tang, Jie Wei

“…However, current diagnostic methods often fall short in early detection and intervention. Machine learning (ML) has shown promise in predicting disease development, yet no relevant predictive models for DOU have been established. …”
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ORGANIZATIONAL AND PEDAGOGICAL CONDITIONS OF USE OF INFORMATION TECHNOLOGIES IN BLENDED LEARNING OF FUTURE OFFICERS by Halus Oleksandr, Kryshchuk Bogdan, Sivak Nataliia

“…The analysis of scientific and pedagogical literature allowed us to note that blended learning is considered as an educational program that includes partially online learning (choice and use of information technologies) and offline learning (controlled by the teacher). …”
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Executive functions in english second language learning: a systematic mapping review = Funções executivas no aprendizado de inglês como segunda língua: um mapeamento sistemático da literatura = Funciones ejecutivas en el aprendizaje del inglés como segundo idioma: un mapeo sistemático de la literatura by Musskopf, Ângela

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Tennis Timing Assessment by a Machine Learning-Based Acoustic Detection System: A Pilot Study by Lucio Caprioli, Amani Najlaoui, Francesca Campoli, Aatheethyaa Dhanasekaran, Saeid Edriss, Cristian Romagnoli, Andrea Zanela, Elvira Padua, Vincenzo Bonaiuto, Giuseppe Annino

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Improving Cognitive and Chemosensory Function in <i>Caenorhabditis elegans</i> Through Polyphenol-Rich Sugarcane Extract by Deniz Heydarian, Matthew Flavel, Mihiri Munasinghe, Markandeya Jois, Jency Thomas

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A New Machine Learning Algorithm for Regional Low-Carbon Economic Development Analysis Based on Data Mining by Xinlei Liu

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Machine Learning and Metabolomics Predict Mesenchymal Stem Cell Osteogenic Differentiation in 2D and 3D Cultures by Michail E. Klontzas, Spyros I. Vernardis, Aristea Batsali, Fotios Papadogiannis, Nicki Panoskaltsis, Athanasios Mantalaris

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Evaluation of hypoglycemic potential of Cuminum cyminum and its role in modulation of cognitive function in rats with induced diabetes by Abhishek Kumar, Amit Shekhar, Mitali Dua, Indu Jangra, Umesh Suranagi, Ekta Arora

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