Search Results - (( (statne OR statnii) python code analysis ) OR ( stat python code analysis ))*

GE-IA-NAM: gene-environment interaction analysis via imaging-assisted neural additive model.

Authors: Li J Xu Y Ma S et al.

Source: Bioinformatics (Oxford, England) [Bioinformatics] 2025 Sep 01; Vol. 41 (9).

Publication Type: Journal Article

Journal Info: Publisher: Oxford University Press Country of Publication: England NLM ID: 9808944 Publication Model: Print Cited Medium: Internet ISSN: 1367-4811 (Electronic) Linking ISSN: 13674803 NLM ISO Abbreviation: Bioinformatics Subsets: MEDLINE

MeSH Terms: Gene-Environment Interaction* , Deep Learning* , Lung Neoplasms*/genetics , Skin Neoplasms*/genetics , Melanoma*/genetics, Datasets as Topic ; Humans ; Age Factors ; Sex Factors ; Smoking

Comparative effectiveness of laparoscopic versus open colectomy in colon cancer patients: a study protocol for emulating a target trial using cancer registry data.

Authors: Abera SF Robers G Kästner A et al.

Source: Journal of cancer research and clinical oncology [J Cancer Res Clin Oncol] 2025 Jan 11; Vol. 151 (1), pp. 34. Date of Electronic Publication: 2025 Jan 11.

Publication Type: Clinical Trial Protocol; Journal Article

Journal Info: Publisher: Springer-Verlag Country of Publication: Germany NLM ID: 7902060 Publication Model: Electronic Cited Medium: Internet ISSN: 1432-1335 (Electronic) Linking ISSN: 01715216 NLM ISO Abbreviation: J Cancer Res Clin Oncol Subsets: MEDLINE

MeSH Terms: Colectomy*/methods , Colonic Neoplasms*/surgery , Colonic Neoplasms*/pathology , Colonic Neoplasms*/mortality , Laparoscopy*/methods, Adult ; Female ; Humans ; Male ; Registries ; Survival Rate ; Clinical Trials, Phase III as Topic ; Randomized Controlled Trials as Topic ; Multicenter Studies as Topic

Primary data for BJC Carbonic anhydrase IX is a pH-stat that sets an acidic tumour extracellular pH in vivo

Authors: Griffiths, JR Lee, Shen-Han McIntyre, Dominick John et al.

Subject Terms: Carbonic anhydrase IX, Extracellular pH, Intracellular pH, ISUCA, Magnetic Resonance Spectroscopy, MRS, pH-stat, Tumour pH

File Description: jMRUI http://www.jmrui.eu/ python www.python.org Excel; application/vnd.openxmlformats-officedocument.spreadsheetml.sheet; application/octet-stream

Relation: https://www.repository.cam.ac.uk/handle/1810/361916; https://doi.org/10.17863/CAM.26029

Availability: https://www.repository.cam.ac.uk/handle/1810/361916
https://doi.org/10.17863/CAM.26029

Sulfur dioxide in the mid-infrared transmission spectrum of WASP-39b.

Authors: Powell D Feinstein AD Lee EKH et al.

Source: Nature [Nature] 2024 Feb; Vol. 626 (8001), pp. 979-983. Date of Electronic Publication: 2024 Jan 17.

Publication Type: Journal Article

Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 0410462 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1476-4687 (Electronic) Linking ISSN: 00280836 NLM ISO Abbreviation: Nature Subsets: PubMed not MEDLINE; MEDLINE

A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula.

Authors: Ince RA Giordano BL Kayser C et al.

Source: Human brain mapping [Hum Brain Mapp] 2017 Mar; Vol. 38 (3), pp. 1541-1573. Date of Electronic Publication: 2016 Nov 17.

Publication Type: Journal Article; Research Support, Non-U.S. Gov't

Journal Info: Publisher: Wiley Country of Publication: United States NLM ID: 9419065 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1097-0193 (Electronic) Linking ISSN: 10659471 NLM ISO Abbreviation: Hum Brain Mapp Subsets: MEDLINE

MeSH Terms: Brain Mapping* , Information Theory* , Normal Distribution*, Brain/*diagnostic imaging , Brain/*physiology , Neuroimaging/*methods, Computer Simulation ; Electroencephalography ; Entropy ; Humans ; Sensitivity and Specificity

Testing Gaussian process with applications to super-resolution

Authors: Jean-Marc Azaïs Yohann De Castro Stéphane Mourareau et al.

Contributors: Jean-Marc Azaïs Yohann De Castro Stéphane Mourareau et al.

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

Subject Terms: FOS: Computer and information sciences, [MATH.MATH-PR] Mathematics [math]/Probability [math.PR], Computer Science - Information Theory, Mathematics - Statistics Theory, Kac-Rice formula, Statistics Theory (math.ST), 01 natural sciences, 94A08, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], 62J05, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], FOS: Mathematics, 62F03, 0101 mathematics, [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, 62H10, 60G10, Mathematics - Probability

File Description: application/pdf

Access URL: https://www.sciencedirect.com/science/article/am/pii/S1063520318301556
http://arxiv.org/abs/1706.00679
https://inria.hal.science/hal-01686434v1/document
https://inria.hal.science/hal-01686434v1
https://www.sciencedirect.com/science/article/pii/S1063520318301556
https://hal-upec-upem.archives-ouvertes.fr/hal-01686434v1
http://dblp.uni-trier.de/db/journals/corr/corr1706.html#AzaisCM17
https://hal.inria.fr/hal-01686434/document
https://arxiv.org/pdf/1706.00679.pdf
https://dblp.uni-trier.de/db/journals/corr/corr1706.html#AzaisCM17
https://hal.science/hal-04955851v1
https://doi.org/10.1016/j.acha.2018.07.001

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

Authors: Fachada, Nuno Fernandes, Daniel Fernandes, Carlos M. et al.

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

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

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

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

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

Subject Terms: 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.

Authors: Stewart, Mathew Peters, Carli Ziegler, Michael J. et al.

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

Genome-wide analyses reveal intricate genetic mechanisms underlying egg production efficiency in chickens.

Authors: Tan, Lizhi Cai, Xinyu Kong, Yuan et al.

Source: Journal of Animal Science & Biotechnology. 8/11/2025, Vol. 16 Issue 1, p1-21. 21p.

Machine learning for prioritizing security code-based Vulnerability discovery

Authors: Ballestas, Rafael García Bedoya, Olmer

Contributors: Ballestas, Rafael García Bedoya, Olmer

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

Subject Terms: Ingeniería, Máquinas, Automatización, Auditorías, Seguridad, Security auditing

Subject Geographic: Colombia

File Description: 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

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

Reducing Stimulant Prescribing Error: A Quality Improvement Initiative in Pediatric Outpatient Setting.

Authors: Watthanathiraphapwong N Traipidok P Charleowsak P et al.

Source: Journal of developmental and behavioral pediatrics : JDBP [J Dev Behav Pediatr] 2024 Jul-Aug 01; Vol. 45 (4), pp. e283-e292. Date of Electronic Publication: 2024 Jun 13.

Publication Type: Journal Article

Journal Info: Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 8006933 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1536-7312 (Electronic) Linking ISSN: 0196206X NLM ISO Abbreviation: J Dev Behav Pediatr Subsets: MEDLINE

MeSH Terms: Quality Improvement*/standards , Attention Deficit Disorder with Hyperactivity*/drug therapy , Central Nervous System Stimulants*/therapeutic use , Medication Errors*/prevention & control, Humans ; Child ; Retrospective Studies ; Male ; Female ; Adolescent ; Ambulatory Care/standards ; Outpatients ; Thailand ; Child, Preschool ; Registries/statistics & numerical data ; Practice Patterns, Physicians'/standards ; Practice Patterns, Physicians'/statistics & numerical data

Strong correlation of gene counts and differentially expressed genes between a 3′ RNA-Seq and an RNA hybridization platform in transcriptome analyses from canine archival tissues.

Authors: Haake, Alexander F. H. Loriani Fard, Alina K. Jovanovic, Vladimir M. et al.

Source: Frontiers in Veterinary Science. 2025, p1-13. 13p.

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

Authors: Csorba, Szilveszter Vribék, Krisztián Farkas, Máté et al.

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

Survival Modelling Using Machine Learning and Immune–Nutritional Profiles in Advanced Gastric Cancer on Home Parenteral Nutrition.

Authors: Matysiak, Konrad Hojdis, Aleksandra Szewczuk, Magdalena

Source: Nutrients. Aug2025, Vol. 17 Issue 15, p2414. 16p.

Unsupervised Voting for Detecting the Algorithmic Solving Strategy in Competitive Programming Solutions.

Authors: Stoica, Alexandru Stefan Babiceanu, Daniel Mihaescu, Marian Cristian et al.

Source: Mathematics (2227-7390); Nov2025, Vol. 13 Issue 22, p3589, 19p

Subject Terms: MACHINE learning, CLUSTERING algorithms, COMPUTER science, ALGORITHMS, SOURCE code

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

Authors: Gautney, Joanna Aguilar, Christina Chan, Julian et al.

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

Inferring leader-follower dynamics in three shark species using acoustic telemetry data.

Authors: Kreuter, Nils Fernández-Gracia, Juan Eguíluz, Víctor M. et al.

Source: Movement Ecology. 8/28/2025, Vol. 13 Issue 1, p1-13. 13p.

Anti-Inflammatory Diet and Probiotic Supplementation as Strategies to Modulate Immune Dysregulation in Autism Spectrum Disorder.

Authors: Naranjo-Galvis, Carlos Andrés Trejos-Gallego, Diana María Correa-Salazar, Cristina et al.

Source: Nutrients. Aug2025, Vol. 17 Issue 16, p2664. 21p.

Official Replication Package of the EMSE Journal Article: 'Does Microservice Adoption Impact the Velocity? A Cohort Study'

Authors: Saarimäki, Nyyti orcid:0000-0001-5538- Robredo, Mikel et al.

Subject Terms: Empirical Software Engineering, Cohort Studies, Microservices Architecture, Development velocity, Velocity

Relation: https://zenodo.org/records/14876472; oai:zenodo.org:14876472; https://doi.org/10.5281/zenodo.14876472

Availability: https://doi.org/10.5281/zenodo.14876472
https://zenodo.org/records/14876472