Výsledky vyhľadávania - ACM: D.: Software/D.1: PROGRAMMING TECHNIQUES/D.1.0: General

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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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    Zdroj: Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1. :135-144

    Popis súboru: application/pdf

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    Zdroj: ISSN: 0304-3975.

    Predmety: Abstraction, Completeness, Induction, Rewriting, Narrowing, Weak termination, ACM: F.: Theory of Computation/F.3: LOGICS AND MEANINGS OF PROGRAMS/F.3.1: Specifying and Verifying and Reasoning about Programs/F.3.1.2: Logics of programs, ACM: F.: Theory of Computation/F.3: LOGICS AND MEANINGS OF PROGRAMS/F.3.1: Specifying and Verifying and Reasoning about Programs/F.3.1.3: Mechanical verification, ACM: D.: Software/D.3: PROGRAMMING LANGUAGES/D.3.1: Formal Definitions and Theory, ACM: D.: Software/D.2: SOFTWARE ENGINEERING/D.2.4: Software/Program Verification/D.2.4.2: Correctness proofs, ACM: D.: Software/D.2: SOFTWARE ENGINEERING/D.2.4: Software/Program Verification/D.2.4.3: Formal methods, ACM: D.: Software/D.2: SOFTWARE ENGINEERING/D.2.4: Software/Program Verification/D.2.4.8: Validation, ACM: F.: Theory of Computation/F.3: LOGICS AND MEANINGS OF PROGRAMS/F.3.1: Specifying and Verifying and Reasoning about Programs/F.3.1.5: Specification techniques, ACM: F.: Theory of Computation/F.4: MATHEMATICAL LOGIC AND FORMAL LANGUAGES/F.4.2: Grammars and Other Rewriting Systems, ACM: F.: Theory of Computation/F.4: MATHEMATICAL LOGIC AND FORMAL LANGUAGES/F.4.3: Formal Languages, ACM: I.: Computing Methodologies/I.1: SYMBOLIC AND ALGEBRAIC MANIPULATION/I.1.3: Languages and Systems/I.1.3.0: Evaluation strategies, ACM: I.: Computing Methodologies/I.1: SYMBOLIC AND ALGEBRAIC MANIPULATION/I.1.3: Languages and Systems/I.1.3.4: Substitution mechanisms, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.2: Automatic Programming/I.2.2.0: Automatic analysis of algorithms, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.2: Automatic Programming/I.2.2.4: Program verification, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.3: Deduction and Theorem Proving/I.2.3.1: Deduction (e.g., natural, rule-based), ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.3: Deduction and Theorem Proving/I.2.3.2: Inference engines, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.3: Deduction and Theorem Proving/I.2.3.4: Mathematical induction, [INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]

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    Zdroj: https://inria.hal.science/inria-00338181 ; [Research Report] 2009, pp.50.

    Predmety: abstraction, induction, innermost, narrowing, ordering constraint, sufficient completeness, weak termination, ACM: F.: Theory of Computation/F.3: LOGICS AND MEANINGS OF PROGRAMS/F.3.1: Specifying and Verifying and Reasoning about Programs/F.3.1.2: Logics of programs, ACM: F.: Theory of Computation/F.3: LOGICS AND MEANINGS OF PROGRAMS/F.3.1: Specifying and Verifying and Reasoning about Programs/F.3.1.3: Mechanical verification, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.3: Deduction and Theorem Proving/I.2.3.2: Inference engines, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.3: Deduction and Theorem Proving/I.2.3.4: Mathematical induction, ACM: D.: Software/D.3: PROGRAMMING LANGUAGES/D.3.1: Formal Definitions and Theory, ACM: D.: Software/D.2: SOFTWARE ENGINEERING/D.2.4: Software/Program Verification/D.2.4.2: Correctness proofs, ACM: D.: Software/D.2: SOFTWARE ENGINEERING/D.2.4: Software/Program Verification/D.2.4.3: Formal methods, ACM: D.: Software/D.2: SOFTWARE ENGINEERING/D.2.4: Software/Program Verification/D.2.4.8: Validation, ACM: F.: Theory of Computation/F.3: LOGICS AND MEANINGS OF PROGRAMS/F.3.1: Specifying and Verifying and Reasoning about Programs/F.3.1.5: Specification techniques, ACM: F.: Theory of Computation/F.4: MATHEMATICAL LOGIC AND FORMAL LANGUAGES/F.4.2: Grammars and Other Rewriting Systems, ACM: F.: Theory of Computation/F.4: MATHEMATICAL LOGIC AND FORMAL LANGUAGES/F.4.3: Formal Languages/F.4.3.0: Algebraic language theory, ACM: I.: Computing Methodologies/I.1: SYMBOLIC AND ALGEBRAIC MANIPULATION/I.1.3: Languages and Systems/I.1.3.0: Evaluation strategies, ACM: I.: Computing Methodologies/I.1: SYMBOLIC AND ALGEBRAIC MANIPULATION/I.1.3: Languages and Systems/I.1.3.4: Substitution mechanisms, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.2: Automatic Programming/I.2.2.0: Automatic analysis of algorithms, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.2: Automatic Programming/I.2.2.4: Program verification, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.3: Deduction and Theorem Proving/I.2.3.1: Deduction (e.g., natural, rule-based), [INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]

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    Prispievatelia: Adam, Michel Frison, Patrice Daoud, Moncef a ďalší

    Relation: info:eu-repo/semantics/altIdentifier/arxiv/2506.03720; ARXIV: 2506.03720

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    Zdroj: Proceedings of the TUG 2011 Conference ; TUG 2011 32nd Annual Meeting of the TeX Users Group ; https://hal.archives-ouvertes.fr/hal-01543098 ; TUG 2011 32nd Annual Meeting of the TeX Users Group , Oct 2011, Trivandrum, India ; http://tug.org/TUGboat/Contents/contents32-3.html

    Geografické téma: Trivandrum, India

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    Prispievatelia: Balabonski, Thibaut Pelle, Robin Rieg, Lionel a ďalší

    Zdroj: ICDCN '18 Proceedings of the 19th International Conference on Distributed Computing and Networking ; ICDCN 2018 - 19th International Conference on Distributed Computing and Networking ; https://hal.sorbonne-universite.fr/hal-01753439 ; ICDCN 2018 - 19th International Conference on Distributed Computing and Networking, Jan 2018, Varanasi, India. pp.1-10, ⟨10.1145/3154273.3154321⟩

    Geografické téma: Varanasi, India

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    Zdroj: Formal and Practical Aspects of Domain-Specific Languages: Recent Developments ; https://hal.archives-ouvertes.fr/hal-01542954 ; Formal and Practical Aspects of Domain-Specific Languages: Recent Developments, 2012, 9781466620926. ⟨10.4018/978-1-4666-2092-6.ch001⟩ ; https://www.igi-global.com/chapter/extensible-languages-blurring-distinction-between/71814

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    Prispievatelia: Shapiro, Marc Bieniusa, Annette Preguiça, Nuno a ďalší

    Zdroj: https://inria.hal.science/hal-01685945 ; [Research Report] RR-9145, Inria Paris; UPMC - Paris 6 Sorbonne Universités; Tech. U. Kaiserslautern; U. Nova de Lisboa; U. Catholique de Louvain. 2018, pp.1-15.

    Relation: info:eu-repo/semantics/altIdentifier/arxiv/1801.06340; info:eu-repo/grantAgreement/EC/FP7/609551/EU/Large-scale computation without synchronisation/SYNCFREE; info:eu-repo/grantAgreement//732505/EU/Lightweight Computation for Networks at the Edge/LightKone; ARXIV: 1801.06340

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