Výsledky vyhľadávania - acm: c.: computer systems organisation/c.4: performance of systems

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    Zdroj: https://hal.univ-reims.fr/tel-01872131 ; Réseaux et télécommunications [cs.NI]. Université de Reims - Champagne Ardenne, 2013.

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    Zdroj: Collecte, filtrage et veille aujourd'hui ; https://inria.hal.science/hal-01255394 ; Université Jean Moulin Lyon3. Mabrouka EL HACHANI (Edt.). Collecte, filtrage et veille aujourd'hui, Jan 2015, Lyon, France. , 2015 ; http://facdeslettres.univ-lyon3.fr/collecte-filtrage-et-veille-aujourd-hui-908047.kjsp?RH=1405931635005

    Geografické téma: Lyon, France

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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

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    Prispievatelia: Sun, Wen Simon, Véronique Monnet, Sébastien a ďalší

    Zdroj: ACM Sigmetrics 2017- International Conference on Measurement and Modeling of Computer Systems ; https://inria.hal.science/hal-01494235 ; ACM Sigmetrics 2017- International Conference on Measurement and Modeling of Computer Systems, Jun 2017, Urbana-Champaign, Illinois, United States. pp.51--51, ⟨10.1145/3078505.3078531⟩ ; http://www.sigmetrics.org/sigmetrics2017/

    Geografické téma: Urbana-Champaign, Illinois, United States

    Relation: info:eu-repo/semantics/altIdentifier/arxiv/1701.00335; ARXIV: 1701.00335

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    Zdroj: https://inria.hal.science/tel-01237164 ; Other [cs.OH]. Université de Rennes 1, 2015.

    Relation: info:eu-repo/grantAgreement//Esprit Project 22729/EU/Optimising Compilers for Embedded Applications/OCEANS; info:eu-repo/grantAgreement//33478/EU/Advanced Compiler Technologies for Embedded Streaming/ACOTES; info:eu-repo/grantAgreement/EC/FP7/214009/EU/Open Media Platform/OMP

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    Zdroj: https://inria.hal.science/tel-04090072 ; Sciences de l'Homme et Société. Université Vincennes Saint-Denis Paris8, 2023.

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    Zdroj: https://hal.archives-ouvertes.fr/tel-01522826 ; Distributed, Parallel, and Cluster Computing [cs.DC]. UPMC - Sorbonne University, 2015.

    Relation: tel-01522826; https://hal.archives-ouvertes.fr/tel-01522826; https://hal.archives-ouvertes.fr/tel-01522826/document; https://hal.archives-ouvertes.fr/tel-01522826/file/hdr-v4.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/chronology%20%281%29.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/chronology.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/cmp.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/complexity%20%281%29.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/complexity.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/composition2%20%281%29.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/composition2.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/histories%20%281%29.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/histories.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/histories2%20%281%29.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/histories2.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/lf-vs-pstm-16384%20%281%29.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/lf-vs-pstm-16384.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/lf-vs-stm-16384%20%281%29.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/lf-vs-stm-16384.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/multiprocessor.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/skiplist_diagram%20%281%29.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/skiplist_diagram.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/tree1%20%281%29.pdf; https://hal.archives-ouvertes.fr/tel-01522826/file/tree1.pdf

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