Suchergebnisse - acm: h.: information system/h.2: database management/h.2.4: system/h.2.4.8: textual databases*

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    Quelle: Communications in Computer and Information Science ; 21st European Conference on Advances in Databases and Information Systems (ADBIS 2017) ; https://hal.science/hal-01529581 ; 21st European Conference on Advances in Databases and Information Systems (ADBIS 2017), Sep 2017, Nicosie, Cyprus. pp.21-28, ⟨10.1007/978-3-319-67162-8⟩ ; http://cyprusconferences.org/adbis2017/

    Geographisches Schlagwort: Nicosie, Cyprus

    Relation: info:eu-repo/semantics/altIdentifier/arxiv/1709.04747; ARXIV: 1709.04747

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    Quelle: 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

    Schlagwörter: 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

    Geographisches Schlagwort: Almaty, Kazakhstan

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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

    Autoren: Okunola, Abiodun

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    Quelle: 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

    Dateibeschreibung: application/pdf

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    Quelle: Actual Problems of the IT, Electronics and Radiotechnics ; https://hal.archives-ouvertes.fr/hal-02019255 ; Actual Problems of the IT, Electronics and Radiotechnics, South Federal University, Dec 2015, Taganrog, Russia. pp.79-81, ⟨10.6084/m9.figshare.7210292⟩

    Schlagwörter: GIS Data Modelling, Database Management, Geodatabase, Database Design, GIS Geographic Information System, Data structures Computer Science, Data structures design and analysis, Data structure, Database Development, Database Management System, ACM: H.: Information Systems, ACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL, 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.2.4: Systems, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.7: Database Administration, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.7: Database Administration/H.2.7.0: Data dictionary/directory, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.8: Database Applications, 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.2.8.3: Spatial databases and GIS, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.8: Database Applications/H.2.8.2: Scientific databases, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO]Computer Science [cs], [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC], [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], [INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]

    Geographisches Schlagwort: Taganrog, Russia

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    Quelle: Future Generation: Ideas of the Young Scientists ; https://hal.archives-ouvertes.fr/hal-02018891 ; Future Generation: Ideas of the Young Scientists, South West State University, Nov 2015, Kursk, Russia. pp.243-246, ⟨10.6084/m9.figshare.7210937⟩ ; https://elibrary.ru/item.asp?id=24992480

    Schlagwörter: GIS Geographic Information System, Geodata spatialization, Geodata discovery, Geodatabase, Marine ecology, GIS Data Modelling, ACM: H.: Information Systems, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT, 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.2.8.2: Scientific databases, 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.2.8.4: Statistical databases, ACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL, ACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.1: Content Analysis and Indexing, ACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.2: Information Storage, ACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.3: Information Search and Retrieval, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.0: General, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.7: Database Administration, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.8: Database Applications, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.7: Database Administration/H.2.7.0: Data dictionary/directory, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DL]Computer Science [cs]/Digital Libraries [cs.DL]

    Geographisches Schlagwort: Kursk, Russia

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