Establishment and validation of predictive model of ARDS in critically ill patients by Senhao Wei, Hua Zhang, Hao Li, Chao Li, Ziyuan Shen, Yiyuan Yin, Zhukai Cong, Zhaojin Zeng, Qinggang Ge, Dongfeng Li, Xi Zhu

“…This study aimed to observe the incidence of ARDS among high-risk patients and develop and validate an ARDS prediction model using machine learning (ML) techniques based on clinical parameters. …”
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Educating the digital generation: the role of virtual communities by E. M. Kharlanova, N. V. Sivrikova, S. V. Roslyakova, E. G. Chernikova

“…It generally implies being involved in several types of virtual communities, spending moderate amount of time in virtual communities, participating in virtual learning societies. Virtual communities have undeniable educational potential. …”
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Professional Action Competence in Education for Sustainability Among Pre-service Physical Education Teachers: A Mixed Method Approach by Valérian Cece, Thomas Royet, Olivier Vors, Vanessa Lentillon-Kaestner

“…This approach emphases the bodily dimension, learning through action, and affective and sensory aspects. …”
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Musician’s dystonia: a perspective on the strongest evidence towards new prevention and mitigation treatments by Joy Grifoni, Joy Grifoni, Valeria Crispiatico, Anna Castagna, Rosa Maria Converti, Marina Ramella, Angelo Quartarone, Teresa L’Abbate, Teresa L’Abbate, Karolina Armonaite, Karolina Armonaite, Luca Paulon, Luca Paulon, Francescaroberta Panuccio, Franca Tecchio

“…To address these challenges, we propose a novel application of the FeeSyCy principle (feedback-synchrony-plasticity), which emphasizes the pivotal role of feedback in guiding inter-neuronal synchronization and plasticity—the foundation of learning and memory. This model integrates with established literature to form a comprehensive framework for understanding MD as an impaired FeeSyCy-mediated relationship between the individual and their environment, ultimately leading to trauma. …”
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Working-memory load decoding model inspired by brain cognition based on cross-frequency coupling by Jing Zhang, Tingyi Tan, Yuhao Jiang, Congming Tan, Liangliang Hu, Daowen Xiong, Yikang Ding, Guowei Huang, Junjie Qin, Yin Tian

“…Therefore, identifying working memory load is an essential area of research. Deep learning models have demonstrated remarkable potential in identifying the intensity of working memory load. …”
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Differences in Characteristics of Peripartum Patients Who Did and Did Not Require an Upgrade to the Intensive Care Unit: A Propensity Score Matching Study by Jennifer A. Walker, Jerry M. Yang, Saad Pirzada, Manahel Zahid, Samantha Asuncion, Amanda Tuchler, Gillian Cooper, Allison Lankford, Emad Elsamadicy, Quincy K. Tran

“…The Classification And Regression Tree, a machine learning algorithm, was used to identify significant predictors of ICU upgrade. …”
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Segmentation of Laser Marks of Diabetic Retinopathy in the Fundus Photographs Using Lightweight U-Net by Yukang Jiang, Jianying Pan, Ming Yuan, Yanhe Shen, Jin Zhu, Yishen Wang, Yewei Li, Ke Zhang, Qingyun Yu, Huirui Xie, Huiting Li, Xueqin Wang, Yan Luo

“…In this study, we develop a deep learning algorithm based on the lightweight U-Net to segment laser marks from the color fundus photos, which could help indicate a stage or providing valuable auxiliary information for the care of DR patients. …”
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Early Transcriptional Changes Induced by Wnt/β-Catenin Signaling in Hippocampal Neurons by Eduardo Pérez-Palma, Víctor Andrade, Mario O. Caracci, Bernabé I. Bustos, Camilo Villaman, Matías A. Medina, Miguel E. Ávila, Giorgia D. Ugarte, Giancarlo V. De Ferrari

“…We also studied molecular networks enriched upon Wnt3a activation and detected three highly significant expression modules involved in glycerolipid metabolic process (GO:0046486, p-adjusted = 4.5 × 10−19), learning or memory (GO:0007611, p-adjusted = 4.0 × 10−5), and neurotransmitter secretion (GO:0007269, p-adjusted = 5.3 × 10−12). …”
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Relationship between stress hyperglycemia ratio and progression of non target coronary lesions: a retrospective cohort study by Shiqi Liu, Ziyang Wu, Gaoliang Yan, Yong Qiao, Yuhan Qin, Dong Wang, Chengchun Tang

“…Logistic regression models, restricted cubic spline analysis, and machine learning algorithms (LightGBM, decision tree, and XGBoost) were utilized to analyse the relationship of stress hyperglycemia ratio and non target lesion progression. …”
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Harmonizing population health data into OMOP common data model: a demonstration using COVID-19 sero-surveillance data from Nairobi Urban Health and Demographic Surveillance System by Michael Ochola, Sylvia Kiwuwa-Muyingo, Tathagata Bhattacharjee, David Amadi, Maureen Ng’etich, Damazo Kadengye, Henry Owoko, Boniface Igumba, Jay Greenfield, Jim Todd, Agnes Kiragga, Agnes Kiragga

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Unfolding insights about resilience and its coping strategies by medical academics and healthcare professionals at their workplaces: a thematic qualitative analysis by Salman Yousuf Guraya, Jacqueline Maria Dias, Mohamed Ahmed Eladl, Ayah Mohammad Rajai Rustom, Fatima Audi Saleem Alalawi, Majid Hassan Saleh Alhammadi, Yusra Ahmed Mohammed Ahmed, Amna Ali Omran Taryam Al Shamsi, Sarah Juman Bilalaga, Alfred Nicholson, Hani Malik, Shaista Salman Guraya

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Transformers for Neuroimage Segmentation: Scoping Review by Maya Iratni, Amira Abdullah, Mariam Aldhaheri, Omar Elharrouss, Alaa Abd-alrazaq, Zahiriddin Rustamov, Nazar Zaki, Rafat Damseh

“…Transformers are a promising deep learning approach for automated medical image segmentation. …”
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Implementasi Metode Analytical Hierarchy Process dan Simple Additive Weighting untuk Pemilihan Dosen Terbaik Studi Kasus STMIK Atma Luhur by Laurentinus laurentinus, Sobirin Rinaldi

“…The criteria are: Education and Learning (C1), Research (C2), Dedication (C3), and Pedagogik (C4) obtained from Ristekdikti. …”
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MLinvitroTox reloaded for high-throughput hazard-based prioritization of high-resolution mass spectrometry data by Katarzyna Arturi, Eliza J. Harris, Lilian Gasser, Beate I. Escher, Georg Braun, Robin Bosshard, Juliane Hollender

“…MLinvitroTox is a machine learning (ML) framework comprising 490 independent XGBoost classifiers trained on molecular fingerprints from chemical structures and target-specific endpoints from the ToxCast/Tox21 invitroDBv4.1 database. …”
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Comparison of the Efficacy of Artificial Intelligence-Powered Software in Crown Design: An In Vitro Study by Ziqiong Wu, Chengqi Zhang, Xinjian Ye, Yuwei Dai, Jing Zhao, Wuyuan Zhao, Yuanna Zheng

“…AI-powered software requires further research and extensive deep learning to improve the morphological accuracy and stability of the crown design.…”
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Implementation of support meetings for patients undergoing outpatient chemotherapy by a multidisciplinary cancer team by Miho Jinno, Misako Dai, Kaori Ito, Yosuke Ando, Seira Toyosato-Nishibe, Maki Akiyoshi, Sachie Noda, Hidezo Matsuda, Naho Tsujii, Miho Zennami, Masami Yamamura, Yoko Katagata, Akemi Ito, Aki Takai, Shigeki Yamada, Kenji Kawada, Junko Sugama, Keiko Mano

“…Patients talked about the value of learning from the experiences of other patients and the easing of loneliness. …”
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Medicinal plants with neuroprotective potential in East African countries: A systematic review by Ibe Michael Usman, Ekom Monday Etukudo, Elna Owembabazi, Wusa Makena, Augustine Oviosun, Makeri Danladi, Vivian Ojiakor, Patrick Maduabuchi Aja, Emeka Anyanwu, Yanurkis Duranones Rosales, Mario Edgar Fernandez Diaz, Josiah Ifie, Ismahil Adekunle Adeniyi, Ilemobayo Victor Fasogbon, Victor Bassey Archibong

“…Behavioral outcomes aligned with these biochemical changes, showing marked improvements in memory and learning, motor activity, seizure threshold, and anxiety-like behavior. …”
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Functional and Cognitive Impairment in Patients with Relapsing–Remitting Multiple Sclerosis: Cognitive Tests and Plasma Neurofilament Light Chain Levels by Elina Polunosika, Joel Simren, Arta Akmene, Nikita Klimovskis, Kaj Blennow, Daina Pastare, Henrik Zetterberg, Renars Erts, Guntis Karelis

“…For the BVMT-R, we found no difference between the two groups; both groups were able to learn the task equally well, but we found a weak correlation between age and learning in both groups, which could be related to the normal aging process. …”
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Vom ›Fremdling‹ zum ›Maßstab‹. Zum Einzug der westlichen Musiktheorie in die arabische Welt bis ins frühe 20. Jahrhundert by Salah Eddin Maraqa

“…. // In the nineteenth century European music became a symbol of progress in the Arab world. Possessing, learning, and playing a European musical instrument became a status symbol that expressed an affiliation with a higher social class. …”
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Intraoperative haemodynamic optimisation using the Hypotension Prediction Index and its impact on tissular perfusion: a protocol for a randomised controlled trial by Javier Ripollés-Melchor, Ane Abad-motos, Juan Victor Lorente, Ignacio Jimenez, Alejandra Becerra, Wilbert Wesselink, Francesca Reguant, Irene Mojarro, Maria de los Angeles Fuentes, Elizabeth Agudelo, Francisco Herrero-Machancoses, Paula Callejo, Joan Bosch, Manuel Ignacio Monge

“…The Hypotension Prediction Index (HPI) developed using machine learning techniques, allows the prediction of arterial hypotension analysing the arterial pressure waveform. …”
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