Výsledky vyhledávání - (( (stateeene OR stat) python code analysis ) OR ( (statnych OR stateeee) python code analysis ))*

A comparison of machine learning algorithms for survival with missing data ; Une comparaison des algorithmes d'apprentissage pour la survie avec données manquantes

Autoři: Dufossé, Paul Benzekry, Sébastien Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO) a další

Přispěvatelé: Dufossé, Paul Benzekry, Sébastien Méthodes computationnelles pour la prise en charge thérapeutique en oncologie : Optimisation des stratégies par modélisation mécaniste et statistique (COMPO) a další

Zdroj: 54es Journées de Statistique de la SFdS
JDS 2023 - 54e Journées de Statistique de la SFds
https://hal.science/hal-04384220
JDS 2023 - 54e Journées de Statistique de la SFds, SFdS, Jul 2023, Bruxelles (BEL), Belgique. ⟨10.48550/arXiv.2303.13590⟩

Témata: Machine Learning (stat.ML), Machine Learning (cs.LG), Machine learning, neural networks, survival data, simulated data, missing data, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [STAT.AP]Statistics [stat]/Applications [stat.AP]

Geografické téma: Bruxelles (BEL), Belgium

Relation: hal-04384220; https://hal.science/hal-04384220; https://hal.science/hal-04384220/document; https://hal.science/hal-04384220/file/preprint_arxiv.pdf

Dostupnost: https://hal.science/hal-04384220
https://hal.science/hal-04384220/document
https://hal.science/hal-04384220/file/preprint_arxiv.pdf
https://doi.org/10.48550/arXiv.2303.13590

Prediction of Positive Patient Health Questionnaire-2 Screening Using Area Deprivation Index in Primary Care.

Autoři: Duarte, Martha Salamanca, Mayra Gonzalez, Juan M. a další

Zdroj: Clinical Nursing Research. Jun2024, Vol. 33 Issue 5, p355-369. 15p.

Témata: *MENTAL depression risk factors, *RISK assessment, *PREDICTION models, *SOCIAL determinants of health, *RECEIVER operating characteristic curves, *QUESTIONNAIRES, *PRIMARY health care, *RETROSPECTIVE studies, *QUANTITATIVE research, *DESCRIPTIVE statistics, *NURSING interventions, *SURVEYS, *HEALTH behavior, *MEDICAL records, *ACQUISITION of data, *SOCIODEMOGRAPHIC factors, *MACHINE learning, *DATA analysis software, *ACCURACY, *COMPARATIVE studies, *SOCIAL classes, *SENSITIVITY & specificity (Statistics), *SOCIAL isolation, *ALGORITHMS, *REGRESSION analysis, *MENTAL depression, *EVALUATION

Geografický termín: FLORIDA

Effects of a post-acute care management program on subsequent acute care utilization for hospitalized patients discharged to skilled nursing facilities.

Autoři: Armstrong D Agovi AM Gehr AW a další

Zdroj: BMC health services research [BMC Health Serv Res] 2026 Jan 07. Date of Electronic Publication: 2026 Jan 07.

Způsob vydávání: Journal Article

Informace o časopise: Publisher: BioMed Central Country of Publication: England NLM ID: 101088677 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1472-6963 (Electronic) Linking ISSN: 14726963 NLM ISO Abbreviation: BMC Health Serv Res Subsets: MEDLINE

Testing Gaussian process with applications to super-resolution

Autoři: Azaïs, Jean-Marc de Castro, Yohann Mourareau, Stéphane a další

Přispěvatelé: Azaïs, Jean-Marc de Castro, Yohann Mourareau, Stéphane a další

Zdroj: Applied and Computational Harmonic Analysis. 48:445-481

Témata: FOS: Computer and information sciences, [MATH.MATH-PR] Mathematics [math]/Probability [math.PR], Computer Science - Information Theory, Gaussian processes, super-resolution, Mathematics - Statistics Theory, Kac-Rice formula, Statistics Theory (math.ST), 01 natural sciences, Parametric hypothesis testing, 94A08, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], 62J05, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], hypothesis testing, FOS: Mathematics, 62F03, 0101 mathematics, Gaussian process, [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST], 62H15, secondary 60E05, Super-Resolution, Information Theory (cs.IT), Probability (math.PR), MSC 2010 subject classifications: Primary 62E15, Hypothesis Testing, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], [MATH.MATH-PR]Mathematics [math]/Probability [math.PR], [INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT], 60G15, 62E15, 62F03, 60G15, 62H10, 62H15 (Primary) 60E05, 60G10, 62J05, 94A08 (secondary), [INFO.INFO-IT] Computer Science [cs]/Information Theory [cs.IT], Gaussian Process, Image processing (compression, reconstruction, etc.) in information and communication theory, 62H10, 60G10, Mathematics - Probability

Popis souboru: application/xml; application/pdf

Přístupová URL adresa: https://www.sciencedirect.com/science/article/am/pii/S1063520318301556
http://arxiv.org/abs/1706.00679
https://zbmath.org/7140143
https://doi.org/10.1016/j.acha.2018.07.001
https://inria.hal.science/hal-01686434v1/document
https://inria.hal.science/hal-01686434v1
https://hal.science/hal-04955851v1
https://doi.org/10.1016/j.acha.2018.07.001

Generation of Scale-Free Assortative Networks via Newman Rewiring for Simulation of Diffusion Phenomena

Autoři: Laura Di Lucchio Giovanni Modanese

Zdroj: Stats, Vol 7, Iss 1, Pp 220-234 (2024)

Témata: assortative networks, Physics - General Physics, General Physics (physics.gen-ph), network rewiring, Statistics, 0103 physical sciences, FOS: Physical sciences, scale-free networks, agent-based models, Bass innovation diffusion model, 01 natural sciences, HA1-4737

Přístupová URL adresa: http://arxiv.org/abs/2310.13716
https://doaj.org/article/1ed58599ad2b446e8fba7bbd67fd64e7

TRIQS/SOM 2.0: Implementation of the stochastic optimization with consistent constraints for analytic continuation.

Autoři: Krivenko, Igor Mishchenko, Andrey S.

Zdroj: Computer Physics Communications. Nov2022, Vol. 280, pN.PAG-N.PAG. 1p.

Témata: *PYTHON programming language, *GREEN'S functions, *MAXIMUM entropy method, *COVARIANCE matrices, *STATISTICAL ensembles, *PROGRAMMING languages, *REGULARIZATION parameter

GPT-4.1 Sets the Standard in Automated Experiment Design Using Novel Python Libraries.

Autoři: Fachada, Nuno Fernandes, Daniel Fernandes, Carlos M. a další

Zdroj: Future Internet; Sep2025, Vol. 17 Issue 9, p412, 28p

Témata: LANGUAGE models, EXPERIMENTAL design, PYTHON programming language, GENERATIVE pre-trained transformers, QUANTITATIVE research, BENCHMARK problems (Computer science), CODE generators

Regularized Maximum Likelihood Estimation for the Random Coefficients Model in Python.

Autoři: Dunker, Fabian Mendoza, Emil Reale, Marco

Zdroj: Mathematics (2227-7390); Dec2025, Vol. 13 Issue 23, p3764, 29p

Témata: PYTHON programming language, MAXIMUM likelihood statistics, CONSUMPTION (Economics), MATHEMATICAL programming, MULTILEVEL models, SCIENTIFIC computing

Portable Electronic Olfactometer for Non-Invasive Screening of Canine Ehrlichiosis: A Proof-of-Concept Study Using Machine Learning.

Autoři: Durán Cotrina, Silvana Valentina Acevedo, Cristhian Manuel Durán Carrillo Gómez, Jeniffer Katerine

Zdroj: Veterinary Sciences. Jan2026, Vol. 13 Issue 1, p88. 20p.

Zinc as a Biomarker of Nutritional Status and Clinical Burden in Recessive Dystrophic Epidermolysis Bullosa: Implications for Preventive Monitoring.

Autoři: Quintana-Castanedo, Lucía Maseda, Rocío Sánchez-Ramón, Silvia a další

Zdroj: Nutrients. Jan2026, Vol. 18 Issue 2, p232. 19p.

Enhanced cattle identification using Siamese network and MobileViT with EMA attention.

Autoři: Han, Mingshuo Li, Baoshan Li, Qi a další

Zdroj: Frontiers in Veterinary Science. 2026, p1-15. 15p.

Cross-domain antimicrobial resistance in poultry farming: A One Health assessment of antimicrobial use and multidrug resistance in Kiambu County, Kenya.

Autoři: Munene, Ann Kangai Mwangi, Peter Muiruri Bebora, Lilly Caroline a další

Zdroj: Veterinary World. Jan2026, Vol. 19 Issue 1, p1-14. 14p.

Témata: Multidrug resistance, Poultry farming, Holism, Enterococcus, Drug resistance in microorganisms, Escherichia coli, Anti-infective agents, Kenyans

Geografický termín: Kenya

Machine learning for prioritizing security code-based Vulnerability discovery

Autoři: Ballestas, Rafael García Bedoya, Olmer

Přispěvatelé: Ballestas, Rafael García Bedoya, Olmer

Zdroj: instname:Universidad de Bogotá Jorge Tadeo Lozano ; reponame:Expeditio Repositorio Institucional UJTL

Témata: Ingeniería, Máquinas, Automatización, Auditorías, Seguridad, Security auditing

Geografické téma: Colombia

Popis souboru: 58 páginas; application/pdf

Relation: Alon, U., Zilberstein, M., Levy, O., and Yahav, E. (2019). code2vec: learning distributed representations of code. Proc. ACM Program. Lang., 3(POPL):1– 29.; Antunes, N. and Vieira, M. (2009). Comparing the Effectiveness of Penetration Testing and Static Code Analysis on the Detection of SQL Injection Vulnerabilities in Web Services. In 2009 15th IEEE Pacific Rim International Symposium on Dependable Computing, pages 301–306, Shanghai, China. IEEE.; Chang, Y., Liu, B., Cong, L., Deng, H., Li, J., and Chen, Y. (2019). Vulnerability Parser: A Static Vulnerability Analysis System for Android Applications. J. Phys.: Conf. Ser., 1288:012053.; Chong, S., Guttman, J., Datta, A., Myers, A., Pierce, B., Schaumont, P., Sherwood, T., and Zeldovich, N. (2016). Report on the NSF Workshop on Formal Methods for Security. arXiv:1608.00678 [cs]. arXiv: 1608.00678.; Dauber, E., Caliskan, A., Harang, R., Shearer, G., Weisman, M., Nelson, F., and Greenstadt, R. (2019). Git Blame Who?: Stylistic Authorship Attribution of Small, Incomplete Source Code Fragments. Proceedings on Privacy Enhancing Technologies, 2019(3):389–408. arXiv: 1701.05681; Ferreira, A. M. and Kleppe, H. (2011). Effectiveness of Automated Application Penetration Testing Tools. Technical report, OS3 University of Amsterdam.; FluidAttacks (2020). Integrates.; Free Software Foundation (2020). GNU diffutils; Ghaffarian, S. M. and Shahriari, H. R. (2017). Software Vulnerability Analysis and Discovery Using Machine-Learning and Data-Mining Techniques: A Survey. ACM Computing Surveys, 50(4):1–36.; Li, Z., Zou, D., Xu, S., Jin, H., Zhu, Y., and Chen, Z. (2018a). SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities. arXiv:1807.06756 [cs, stat]. arXiv: 1807.06756.; Li, Z., Zou, D., Xu, S., Ou, X., Jin, H., Wang, S., Deng, Z., and Zhong, Y. (2018b). VulDeePecker: A Deep Learning-Based System for Vulnerability Detection. Proceedings 2018 Network and Distributed System Security Symposium. arXiv: 1801.01681.; Moor, O. d., Verbaere, M., Hajiyev, E., Avgustinov, P., Ekman, T., Ongkingco, N., Sereni, D., and Tibble, J. (2007). Keynote Address: .QL for Source Code Analysis. In Seventh IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM 2007), pages 3–16, Paris, France. IEEE; Ng, A. (2016). What Artificial Intelligence Can and Can’t Do Right Now. Harvard Business Review. Section: Analytics.; 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., and Duchesnay, E. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12:2825–2830.; Rice, H. G. (1953). Classes of recursively enumerable sets and their decision problems. Trans. Amer. Math. Soc., 74(2):358–366.; Schwartz, E. J., Avgerinos, T., and Brumley, D. (2010). All You Ever Wanted to Know about Dynamic Taint Analysis and Forward Symbolic Execution (but Might Have Been Afraid to Ask). In 2010 IEEE Symposium on Security and Privacy, pages 317–331, Oakland, CA, USA. IEEE.; Sommer, R. and Paxson, V. (2010). Outside the Closed World: On Using Machine Learning for Network Intrusion Detection. In 2010 IEEE Symposium on Security and Privacy, pages 305–316, Oakland, CA, USA. IEEE.; Stefinko, Y., Piskozub, A., and Banakh, R. (2016). Manual and automated penetration testing. Benefits and drawbacks. Modern tendency. In 2016 13th International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science (TCSET), pages 488–491, Lviv, Ukraine. IEEE.; Yamaguchi, F., Wressnegger, C., Gascon, H., and Rieck, K. (2013). Chucky: exposing missing checks in source code for vulnerability discovery. In Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security - CCS ’13, pages 499–510, Berlin, Germany. ACM Press.; http://hdl.handle.net/20.500.12010/17241; http://expeditio.utadeo.edu.co

Dostupnost: https://hdl.handle.net/20.500.12010/17241
http://expeditio.utadeo.edu.co

A statistical approach to automated analysis of the low‐contrast object detectability test for the large ACR MRI phantom.

Autoři: Golestani, Ali M. Gee, Julia M.

Zdroj: Journal of Applied Clinical Medical Physics; Jul2025, Vol. 26 Issue 7, p1-9, 9p

Témata: LINEAR statistical models, IMAGING phantoms, QUALITY control, PYTHON programming language, MAGNETIC resonance imaging

The state of the late Quaternary megafauna extinction debate: a systematic review and analysis.

Autoři: Stewart, Mathew Peters, Carli Ziegler, Michael J. a další

Zdroj: Frontiers in Mammal Science. 2025, p1-27. 27p.

Data-Driven Early Warning Approach for Antimicrobial Resistance Prediction–Anomaly Detection Based on High-Level Indicators.

Autoři: Csorba, Szilveszter Vribék, Krisztián Farkas, Máté a další

Zdroj: Veterinary Sciences. Oct2025, Vol. 12 Issue 10, p935. 17p.

Sex-Specific Dietary Predictors of Blood Glucose Identified Through Decision Tree Modeling in Adults.

Autoři: Gautney, Joanna Aguilar, Christina Chan, Julian a další

Zdroj: Nutrients. Oct2025, Vol. 17 Issue 19, p3119. 12p.

Comparative virulence study of locally circulating peste des petits ruminants virus (PPRV) strains in indigenous Ethiopian goats.

Autoři: Aklilu, Fasil Ashenafi, Hagos Kassa, Tesfu a další

Zdroj: BMC Veterinary Research. 10/6/2025, Vol. 21 Issue 1, p1-11. 11p.

Témata: Peste des petits ruminants, Microbial virulence, Symptoms, Goats, Comparative studies, Seroconversion, Communicable disease control

Geografický termín: Ethiopia

ASPA 25th Congress Book of Abstract.

Autoři: Renna, Manuela (AUTHOR) manuela.renna@unito.it

Zdroj: Italian Journal of Animal Science. 2025 Suppl 1, Vol. 24 Issue 1, p1-463. 463p.

Sweet Taste Adaptation to Sugars, Sucralose, and Their Blends: A Human and Rodent Perspective.

Autoři: Okoye, Stephanie I. Kim, Minjae Petty, Sara a další

Zdroj: Nutrients. Oct2025, Vol. 17 Issue 19, p3075. 16p.