Showing 13,921 - 13,940 results of 15,418 for search '"learning"', query time: 0.13s Refine Results
  1. 13921
  2. 13922

    An atmospheric correction method for Himawari-8 imagery based on a multi-layer stacking algorithm by Menghui Wang, Donglin Fan, Hongchang He, You Zeng, Bolin Fu, Tianlong Liang, Xinyue Zhang, Wenhan Hu

    Published 2025-03-01
    “…For comparative analysis, a near-infrared–shortwave infrared AC method and a general machine learning AC method were also implemented. Model evaluation and validation were performed using a test subset of simulated data and in-situ datasets. …”
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    Article
  3. 13923
  4. 13924

    Effects of Teenage Pregnancy on Girl Child Education in Buhunga Sub-County Uganda. by Twikirize, Edwig

    Published 2025
    “…School leaders facilitate the teachers, the students, and the community to embrace a hospitable, empathetic, and collaborative learning environment for the different students irrespective of their diversity. …”
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    Thesis
  5. 13925

    Manual of Clinical anesthesiology :

    Published 2021
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    Book
  6. 13926

    Att lära om naturen från naturen och i naturen by Sara Planting-Bergloo, Emma Rova, Charlotte Lennartsdotter, Per Rohlin, Maria Andrée

    Published 2025-02-01
    “…Studien kan vidare fungera som ett stöd för lärare hur man explicit kan adressera dessa fältpraktiker i undervisningen – inför, under och efter genomförande av fältstudier. Learning about nature from nature in nature: Knowledge interests in lower secondary school Biology field work This study focuses on the role of scientific inquiry in outdoor lower secondary Biology education. …”
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    Article
  7. 13927

    Impaired cognitive function and decreased monoamine neurotransmitters in the DNAJC12 gene knockout mouse model by Shunan Wang, Ming Shen, Bo Pang, Bo Zhou, Yuan Yuan, Mei Lu, Xiangling Deng, Min Yang, Shufang Liu, Qiong Wang, Mei Xue, Qisheng Xia, Zhixin Zhang

    Published 2025-02-01
    “…These knockout mice showed significant deficits in learning and memory performance as assessed by the Morris water maze test. …”
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    Article
  8. 13928

    Accessible model predicts response in hormone receptor positive HER2 negative breast cancer receiving neoadjuvant chemotherapy by Luca Mastrantoni, Giovanna Garufi, Giulia Giordano, Noemi Maliziola, Elena Di Monte, Giorgia Arcuri, Valentina Frescura, Angelachiara Rotondi, Armando Orlandi, Luisa Carbognin, Antonella Palazzo, Federica Miglietta, Letizia Pontolillo, Alessandra Fabi, Lorenzo Gerratana, Sergio Pannunzio, Ida Paris, Sara Pilotto, Fabio Marazzi, Antonio Franco, Gianluca Franceschini, Maria Vittoria Dieci, Roberta Mazzeo, Fabio Puglisi, Valentina Guarneri, Michele Milella, Giovanni Scambia, Diana Giannarelli, Giampaolo Tortora, Emilio Bria

    Published 2025-02-01
    “…We developed a framework to predict pCR using clinicopathological characteristics widely available at diagnosis. The machine learning (ML) models were trained to predict pCR (n = 463), evaluated in an internal validation cohort (n = 109) and validated in an external validation cohort (n = 151). …”
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    Article
  9. 13929

    An interactive course program on nutrition for medical students: interdisciplinary development and mixed-methods evaluation by Gonza B. Ngoumou, Daniela A. Koppold, Laetitia Wenzel, Anne Schirmaier, Carolin Breinlinger, Lisa M. Pörtner, Stefan Jordan, Julia K. Schiele, Etienne Hanslian, Annika Koppold, Beate Stock-Schröer, Dimitra M. Varvarezou, Michael Jeitler, Miriam Ortiz, Andreas Michalsen, Wiebke Stritter, Georg Seifert, Christian S. Kessler

    Published 2025-01-01
    “…The conceptualisation resulted in a highly participative two-week course of 37.5 h. The main learning objectives aimed at the acquisition of technical competences and personal competencies in four areas: (1) the role of nutrition in health and disease; (2) the exploration of global food systems; (3) communication on subjects of nutrition; (4) culinary medicine. …”
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    Article
  10. 13930

    Exploring sex differences in Alzheimer’s disease: a comprehensive analysis of a large patient cohort from a memory unit by Maitee Rosende-Roca, Fernando García-Gutiérrez, Yahveth Cantero-Fortiz, Montserrat Alegret, Vanesa Pytel, Pilar Cañabate, Antonio González-Pérez, Itziar de Rojas, Liliana Vargas, Juan Pablo Tartari, Ana Espinosa, Gemma Ortega, Alba Pérez-Cordón, Mariola Moreno, Sílvia Preckler, Susanna Seguer, Miren Jone Gurruchaga, Lluís Tárraga, Agustín Ruiz, Sergi Valero, Mercè Boada, Marta Marquié

    Published 2025-01-01
    “…We employed various statistical techniques to assess the impact of sex on cognitive evolution in these dementia patients, accounting for other sex-related risk factors identified through Machine Learning methods. Results The study cohort comprised a total of 6108 individuals diagnosed with AD dementia during the study period (28.4% males and 71.6% females). …”
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    Article
  11. 13931

    Risk Factors for Gastrointestinal Bleeding in Patients With Acute Myocardial Infarction: Multicenter Retrospective Cohort Study by Yanqi Kou, Shicai Ye, Yuan Tian, Ke Yang, Ling Qin, Zhe Huang, Botao Luo, Yanping Ha, Liping Zhan, Ruyin Ye, Yujie Huang, Qing Zhang, Kun He, Mouji Liang, Jieming Zheng, Haoyuan Huang, Chunyi Wu, Lei Ge, Yuping Yang

    Published 2025-01-01
    “…ObjectiveThis study aimed to develop and validate a machine learning (ML)–based model for predicting in-hospital GIB in patients with AMI, identify key risk factors, and evaluate the clinical applicability of the model for risk stratification and decision support. …”
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    Article
  12. 13932

    Fatty Acids of Erythrocyte Membranes and Blood Serum in Differential Diagnosis of Inflammatory Bowel Diseases by M. V. Kruchinina, I. O. Svetlova, M. F. Osipenko, N. V. Abaltusova, A. A. Gromov, M. V. Shashkov, A. S. Sokolova, I. N. Yakovina, A. V. Borisova

    Published 2022-12-01
    “…The study of FA levels in groups with different nosological forms of IBDs using complex statistical analysis, including machine learning methods, made it possible to create diagnostic models that differentiate CD, UC and UCC in the acute stage with high accuracy. …”
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    Article
  13. 13933

    Therapeutic effect of dihydroartemisinin on Alzheimer’s disease model mice with senile macular degeneration by Gao Han, Gong Xuewu, Zhang Meng, Wang Yuejing, Wang Yuchun, Zhang Keshuang, Yao Hongbo

    Published 2025-02-01
    “…Morris water maze was used to detect the spatial learning and memory ability of AD mice. Hematoxylin eosin (he) staining was used to observe the structural changes of cerebral cortical neurons and retina, and transmission electron microscope was used to observe the structural changes of mitochondria and synapses. …”
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    Article
  14. 13934

    Integrating pharmacogenomics and cheminformatics with diverse disease phenotypes for cell type-guided drug discovery by Arda Halu, Sarvesh Chelvanambi, Julius L. Decano, Joan T. Matamalas, Mary Whelan, Takaharu Asano, Namitra Kalicharran, Sasha A. Singh, Joseph Loscalzo, Masanori Aikawa

    Published 2025-01-01
    “…Pathopticon demonstrates a better prediction performance than solely cheminformatic measures as well as state-of-the-art network and deep learning-based methods. Top predictions made by Pathopticon have high chemical structural diversity, suggesting their potential for building compound libraries. …”
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    Article
  15. 13935

    Knowledge Distillation in Object Detection for Resource-Constrained Edge Computing by Arief Setyanto, Theopilus Bayu Sasongko, Muhammad Ainul Fikri, Dhani Ariatmanto, I. Made Artha Agastya, Rakandhiya Daanii Rachmanto, Affan Ardana, In Kee Kim

    Published 2025-01-01
    “…Although state-of-the-art deep learning-based OD methods achieve high detection rates, their large model size and high computational demands often hinder deployment on resource-constrained edge devices. …”
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    Article
  16. 13936

    Dealing with Complexity – Knowledge, design, and management of the built environment by Cesare Sposito, Francesca Scalisi

    Published 2024-12-01
    “…How do we place knowledge and learning into a system to better understand the current era’s multidimensional, fundamental, and global issues in their irreducible complexity? …”
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    Article
  17. 13937

    A consensus statement on child and family health during the COVID-19 pandemic and recommendations for post-pandemic recovery and re-build by Caroline A. B. Redhead, Sergio A. Silverio, Sergio A. Silverio, Elana Payne, Elana Payne, Mari Greenfield, Mari Greenfield, Sara M. Barnett, Anna Chiumento, Beth Holder, Helen Skirrow, Ofelia Torres, Carmen Power, Staci M. Weiss, Laura A. Magee, Soo Downe, Lucy Frith, Claire Cameron

    Published 2025-01-01
    “…We have identified and agreed priorities areas for both action and learning, which we present as recommendations for research, healthcare practice, and policy.ResultsThe synthesis led to immediate recommendations grouped around what to retain and what to remove from “pandemic” provision and what to reinstate from pre-pandemic, healthcare provision in these services. …”
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    Article
  18. 13938
  19. 13939

    Monitoring Over Time of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Patients Through an Ensemble Vision Transformers‐Based Model by Maria Colomba Comes, Annarita Fanizzi, Samantha Bove, Luca Boldrini, Agnese Latorre, Deniz Can Guven, Serena Iacovelli, Tiziana Talienti, Alessandro Rizzo, Francesco Alfredo Zito, Raffaella Massafra

    Published 2024-12-01
    “…Aims This study aimed to develop an ensemble deep learning‐based model, exploiting a Vision Transformer (ViT) architecture, which merges features automatically extracted from five segmented slices of both pre‐ and mid‐treatment exams containing the maximum tumor area, to predict and monitor pCR to NAC. …”
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    Article
  20. 13940

    A novel α-conotoxin [D1G, ΔQ14] LvIC decreased mouse locomotor activity by Wen Wang, Wen Wang, Meiting Wang, Huanbai Wang, Weifeng Xu, Conggang Wang, Jie Pei, Xiaodan Li, Dongting Zhangsun, Dongting Zhangsun

    Published 2025-01-01
    “…Despite these changes, results from the Morris water maze (MWM) indicated that [D1G, ΔQ14] LvIC did not impair the learning and memory abilities of the mice.ConclusionOur findings indicate that α-conotoxin [D1G, ΔQ14] LvIC significantly decreased locomotor activity in mice. …”
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    Article