Výsledky vyhledávání - acm: h.: information system/h.2: database management/h.2.4: system/h.2.4.4: parallel databases

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    1. American Heart Association. (2021). Heart disease and stroke statistics—2021 update. Circulation, 143(8), e254-e743. 2. Rahman, M., Al Amin, M., Hasan, R., Hossain, S. T., Rahman, M. H., & Rashed, R. A. M. (2025). A Predictive AI Framework for Cardiovascular Disease Screening in the US: Integrating EHR Data with Machine and Deep Learning Models. British Journal of Nursing Studies, 5(2), 40-48. 3. ZakirHossain, M., Khan, M. M., Thapa, S., Uddin, R., Meem, E. J., Niloy, S. K., ... & Bhavani, G. D. (2025, February). Advanced Deep Learning Techniques for Precision Diagnosis of Tea Leaf Diseases. In 2025 IEEE International Conference on Emerging Technologies and Applications (MPSec ICETA) (pp. 1-6). IEEE. 4. Chen, T., & Guestrin, C. (2016). XGBoost: A scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining (pp. 785-794). ACM. 5. Damen, J. A., Hooft, L., Schuit, E., Debray, T. P., Collins, G. S., Tzoulaki, I., Lassale, C. M., Siontis, G. C., Chiocchia, V., Roberts, C., Schlüssel, M. M., Gerry, S., Black, J. A., Heus, P., van der Schouw, Y. T., Peelen, L. M., & Moons, K. G. (2016). Prediction models for cardiovascular disease risk in the general population: systematic review. BMJ, 353, i2416. 6. Framingham Heart Study. (1948). Framingham Heart Study cohort research data. National Heart, Lung, and Blood Institute. 7. Johnson, A. E., Pollard, T. J., Shen, L., Lehman, L. H., Feng, M., Ghassemi, M., Moody, B., Szolovits, P., Celi, L. A., & Mark, R. G. (2016). MIMIC-III, a freely accessible critical care database. Scientific Data, 3, 160035. 8. Krittanawong, C., Zhang, H., Wang, Z., Aydar, M., & Kitai, T. (2017). Artificial intelligence in precision cardiovascular medicine. Journal of the American College of Cardiology, 69(21), 2657-2664. 9. Lundberg, S. M., & Lee, S. I. (2017). A unified approach to interpreting model predictions. In Advances in Neural Information Processing Systems 30 (NIPS 2017) (pp. 4765-4774). 10. Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., & Duchesnay, É. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12, 2825–2830. 11. Shameer, K., Johnson, K. W., Glicksberg, B. S., Dudley, J. T., & Sengupta, P. P. (2018). Machine learning in cardiovascular medicine: are we there yet? Heart, 104(14), 1156-1164. 12. Steyerberg, E. W., Vergouwe, Y., & van Calster, B. (2019). Towards better clinical prediction models: seven steps for development and an ABCD for validation. European Heart Journal, 40(15), 1255–1264. 13. Sudlow, C., Gallacher, J., Allen, N., Beral, V., Burton, P., Danesh, J., Downey, P., Elliott, P., Green, J., Landray, M., Liu, B., Matthews, P., Ong, G., Pell, J., Silman, A., Young, A., Sprosen, T., Peakman, T., & Collins, R. (2015). UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLOS Medicine, 12(3), e1001779. 14. Weng, S. F., Reps, J., Kai, J., Garibaldi, J. M., & Qureshi, N. (2017). Can machine-learning improve cardiovascular risk prediction using routine clinical data? PLOS ONE, 12(4), e0174944. 15. World Health Organization. (2021). Cardiovascular diseases (CVDs). Retrieved from https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds) 16. Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., Devin, M., Ghemawat, S., Irving, G., Isard, M., Kudlur, M., Levenberg, J., Monga, R., Moore, S., Murray, D. G., Steiner, B., Tucker, P., Vasudevan, V., Warden, P., ... Zheng, X. (2016). TensorFlow: A system for large-scale machine learning. In 12th USENIX symposium on operating systems design and implementation (OSDI 16) (pp. 265–283). 17. Chollet, F. (2015). Keras (Version 2.4.0) [Computer software]. https://github.com/fchollet/keras

    Autoři: Okunola, Abiodun

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    Zdroj: Amer-Yahia, S, Amsterdamer, Y, Bhowmick, S S, Bonifati, A, Bonnet, P, Borovica-Gajic, R, Catania, B, Cerquitelli, T, Chiusano, S, Chrysanthis, P K, Curino, C, Darmont, J, Abbadi, A E, Floratou, A, Freire, J, Jindal, A, Kalogeraki, V, Koutrika, G, Kumar, A, Maiyya, S, Meliou, A, Mohanty, M, Naumann, F, Noack, N S, Özcan, F, Peterfreund, L, Rahayu, W, Tan, W-C, Tian, Y, Tözün, P, Vargas-Solar, G, Yadwadkar, N J & Zhang, M 2022, 'Diversity and Inclusion Activities in Database Conferences: A 2021 Report', S I G M O D Record, vol. 51, no. 2, pp. 69-73. https://doi.org/10.1145/3552490.3552510

    Popis souboru: application/pdf

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    Autoři: Hupfeld F. Cortes T. Kolbeck B. a další

    Přispěvatelé: Hupfeld F. Cortes T. Kolbeck B. a další

    Zdroj: Concurrency and computation 20 (2008): 2049–2060. doi:10.1002/cpe.1304
    info:cnr-pdr/source/autori:Felix Hupfeld; Toni Cortes; Björn Kolbeck; Erich Focht; Matthias Hess; Jesús Malo; Jonathan Martí; Eugenio Cesario/titolo:The XtreemFS architecture-a case object-based file systems in Grids/doi:10.1002%2Fcpe.1304/rivista:Concurrency and computation/anno:2008/pagina_da:2049/pagina_a:2060/intervallo_pagine:2049–2060/volume:20
    Paton, N W 2008, Autonomies and data management. in Concurrency Computation Practice and Experience|Concurrency Comput. Pract. Exper.. vol. 20, John Wiley & Sons Ltd, pp. 2075-2088, 4th VLDB Workshop on Secure Data Management, Vienna, AUSTRIA, 23/09/07. https://doi.org/10.1002/cpe.1306
    Paton, N W 2008, 'Autonomies and data management', Concurrency and Computation: Practice & Experience, vol. 20, no. 17, pp. 2075-2088. https://doi.org/10.1002/cpe.1306

    Přístupová URL adresa: http://documents.epfl.ch/users/d/de/desousa/www/papers/nsantos07ReplicationSecurity.pdf
    https://research.manchester.ac.uk/en/publications/1956e428-39a8-4aa1-b9fa-3e61eb49a141
    https://doi.org/10.1002/cpe.1306
    https://research.manchester.ac.uk/en/publications/1c17e6c3-d4b4-454e-94bf-64cf2dc1dcf4
    https://doi.org/10.1002/cpe.1306
    https://inria.hal.science/inria-00482185v1
    https://doi.org/10.1002/cpe.1303
    https://iris.unical.it/handle/20.500.11770/303505
    https://onlinelibrary.wiley.com/doi/10.1002/cpe.1304
    http://www.xtreemfs.org/publications/hupfeld_casefs_journal_online.pdf
    https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.140.3732&rep=rep1&type=pdf
    http://www.storagebox.org/private/felix/hupfeld_casefs_journal_online.pdf
    https://doi.org/10.1002/cpe.1304
    https://www.escholar.manchester.ac.uk/uk-ac-man-scw:2f120
    https://www.research.manchester.ac.uk/portal/en/publications/autonomies-and-data-management(1c17e6c3-d4b4-454e-94bf-64cf2dc1dcf4).html
    https://dblp.uni-trier.de/db/journals/concurrency/concurrency20.html#RablPK08
    http://www.fim.uni-passau.de/fileadmin/files/lehrstuhl/kosch/Papers/2007/DynamicClusterDB-VLDB-DMG-2007.pdf
    http://onlinelibrary.wiley.com/doi/10.1002/cpe.1302/abstract
    http://dblp.uni-trier.de/db/journals/concurrency/concurrency20.html#RablPK08
    https://dl.acm.org/doi/10.5555/1455696.1455702
    http://onlinelibrary.wiley.com/doi/10.1002/cpe.1304/abstract;jsessionid=1708FB2EC8B3B12AD86FB5658DCCD822.d01t01
    https://hdl.handle.net/20.500.14243/118969
    https://doi.org/10.1002/cpe.1304
    https://hdl.handle.net/20.500.11770/303505
    https://doi.org/10.1002/cpe.1304
    https://research.manchester.ac.uk/en/publications/1c17e6c3-d4b4-454e-94bf-64cf2dc1dcf4
    http://www3.interscience.wiley.com/cgi-bin/fulltext/117935420/PDFSTART
    https://doi.org/10.1002/cpe.1306
    http://dblp.uni-trier.de/rec/bibtex/journals/concurrency/Paton08.xml
    http://www3.interscience.wiley.com/cgi-bin/fulltext/117935420/PDFSTART
    http://dblp.uni-trier.de/db/journals/concurrency/concurrency20.html#Paton08
    http://dblp.uni-trier.de/rec/bibtex/journals/concurrency/Paton08
    https://research.manchester.ac.uk/en/publications/1956e428-39a8-4aa1-b9fa-3e61eb49a141
    https://doi.org/10.1002/cpe.1306

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    Zdroj: 3rd International Farabi Readings. 'Green Bridge Through Generations'
    https://hal.archives-ouvertes.fr/hal-01973112
    3rd International Farabi Readings. 'Green Bridge Through Generations', Al-Farabi Kazakh National University, Apr 2016, Almaty, Kazakhstan. pp.349-353, ⟨10.6084/m9.figshare.7210238⟩
    http://greenbridgework.kaznu.kz/?page_id=238

    Témata: Data structures Computer Science, Data organization, Structural Analysis, Data management system, Data management, Data access, Data acquisition, Data manipulaiton, Table structure, Table Extraction, environmental measurement, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.8: Database Applications/H.2.8.3: Spatial databases and GIS, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.8: Database Applications/H.2.8.2: Scientific databases, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.8: Database Applications/H.2.8.0: Data mining, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.8: Database Applications/H.2.8.4: Statistical databases, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.0: General, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.4: Systems, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.4: Systems/H.2.4.3: Object-oriented databases, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.4: Systems/H.2.4.6: Relational databases, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.5: Heterogeneous Databases/H.2.5.0: Data translation, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.7: Database Administration, [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC], [INFO.EIAH]Computer Science [cs]/Technology for Human Learning, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], [INFO.INFO-DL]Computer Science [cs]/Digital Libraries [cs.DL], [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing

    Geografické téma: Almaty, Kazakhstan

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    Zdroj: Herrmann, K, Voigt, H, Behrend, A, Rausch, J & Lehner, W 2017, Living in parallel realities-Co-existing schema versions with a bidirectional database evolution language. in SIGMOD 2017-Proceedings of the 2017 ACM International Conference on Management of Data. Association for Computing Machinery, Proceedings of the ACM SIGMOD International Conference on Management of Data, vol. Part F127746, pp. 1101-1116, 2017 ACM SIGMOD International Conference on Management of Data, SIGMOD 2017, Chicago, United States, 14/05/2017. https://doi.org/10.1145/3035918.3064046

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