Search Results - ACM: C.: Computer Systems Organization/C.0: GENERAL/C.0.3: System architektura*

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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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    Alternate Title: WYMAGANIA I ARCHITEKTURA SYSTEMU PŁATNOŚCI W INTERNECIE PRZYSZŁOŚCI. (Polish)

    Source: Business Informatics / Informatyka Ekonomiczna; 2012, Vol. 2 Issue 24, p91-103, 13p

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    Transliterated Title: Projekt Hansa-East otwarta architektura szpitalnych systemów informatycznych--pierwsze doniesienie.

    Authors: Borkowski W; Zakład Zdrowia Publicznego i Medycyny Szkolnej, Instytut Matki i Dziecka w Warszawie.

    Source: Medycyna wieku rozwojowego [Med Wieku Rozwoj] 1999 Oct-Dec; Vol. 3 (4), pp. 605-13.

    Publication Type: English Abstract; Journal Article

    Journal Info: Publisher: Blue Sparks Pub. Group Country of Publication: Poland NLM ID: 100928610 Publication Model: Print Cited Medium: Print NLM ISO Abbreviation: Med Wieku Rozwoj Subsets: MEDLINE

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    Source: EJDE "Electronic Journal of Digital Enterprise (ISSN: 1776-2960)" ; https://inria.hal.science/hal-00783274 ; Academic e-Journal eJ.D.E. EJDE "Electronic Journal of Digital Enterprise (ISSN: 1776-2960)", Mar 2011, Montpellier, France. pp.1-7

    Subject Geographic: Montpellier, France

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    Source: 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/

    Subject Geographic: Urbana-Champaign, Illinois, United States

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

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    Authors: Volkelt, Johannes Immanuel, 1848-1930, Auteur du texte

    Source: Bibliothèque nationale de France, département Philosophie, histoire, sciences de l'homme, 4-R-3004 (3), 1925-1927.

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    Authors: Volkelt, Johannes Immanuel, 1848-1930, Auteur du texte

    Source: Bibliothèque nationale de France, département Philosophie, histoire, sciences de l'homme, 4-R-3004 (1), 1925-1927.

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    Authors: Volkelt, Johannes Immanuel, 1848-1930, Auteur du texte

    Source: Bibliothèque nationale de France, département Philosophie, histoire, sciences de l'homme, 4-R-3004 (2), 1925-1927.

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    Authors: Rickert, Heinrich, 1863-1936, Auteur du texte

    Source: Bibliothèque nationale de France, département Philosophie, histoire, sciences de l'homme, Z KOJEVE-3611, 1921.

    Relation: Notice du catalogue : http://catalogue.bnf.fr/ark:/12148/cb40940976k