Suchergebnisse - (( (stat OR stavebne) python code analysis ) OR ( stateen python code analysis ))*

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

Autoren: Li J Xu Y Ma S et al.

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

Publikationsart: Journal Article

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

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

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

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

Schlagwörter: 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.

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

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

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

Python Programming: Numerical Analysis/Machine Learning Series.

Autoren: Doskas, Constantinos

Quelle: ISSA Journal; Oct2023, Vol. 21 Issue 10, p34-38, 5p

Schlagwörter: PYTHON programming language, NUMERICAL analysis, MACHINE learning

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

Autoren: Dunker, Fabian Mendoza, Emil Reale, Marco

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

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

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

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

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

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

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

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

Automation of Software Code Analysis Using Machine Learning Methods.

Autoren: Moshkin, V. S. Dyrnochkin, A. A. Yarushkina, N. G.

Quelle: Pattern Recognition & Image Analysis; Sep2023, Vol. 33 Issue 3, p417-424, 8p

Time Series Analysis with Python Cookbook : Practical Recipes for the Complete Time Series Workflow, From Modern Data Engineering to Advanced Forecasting and Anomaly Detection

Autoren: Tarek A. Atwan

Resource Type: eBook.

Categories: COMPUTERS / Data Science / Data Modeling & Design, COMPUTERS / Data Science / General, COMPUTERS / Data Science / Data Analytics

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.

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

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

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

Autoren: Duarte, Martha Salamanca, Mayra Gonzalez, Juan M. et al.

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

Schlagwörter: *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

Geografische Kategorien: FLORIDA

Extended sample size calculations for evaluation of prediction models using a threshold for classification.

Autoren: Whittle R Ensor J Archer L et al.

Quelle: BMC medical research methodology [BMC Med Res Methodol] 2025 Jul 01; Vol. 25 (1), pp. 170. Date of Electronic Publication: 2025 Jul 01.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: BioMed Central Country of Publication: England NLM ID: 100968545 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2288 (Electronic) Linking ISSN: 14712288 NLM ISO Abbreviation: BMC Med Res Methodol Subsets: MEDLINE

MeSH-Schlagworte: Models, Statistical*, Sample Size ; Humans ; Predictive Value of Tests ; Risk Assessment/methods ; Sensitivity and Specificity ; Algorithms

SparseCoder: Advancing source code analysis with sparse attention and learned token pruning.

Autoren: Yang, Xueqi Jakubowski, Mariusz Kang, Li et al.

Quelle: Empirical Software Engineering; Feb2025, Vol. 30 Issue 1, p1-30, 30p

Prediction of Chemically Modified Antimicrobial Peptides and Their Sub-functional Activities Using Hybrid Features.

Autoren: Yao Y Zhang D Fan H et al.

Quelle: Probiotics and antimicrobial proteins [Probiotics Antimicrob Proteins] 2025 May 21. Date of Electronic Publication: 2025 May 21.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Springer Country of Publication: United States NLM ID: 101484100 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1867-1314 (Electronic) Linking ISSN: 18671306 NLM ISO Abbreviation: Probiotics Antimicrob Proteins Subsets: MEDLINE

Compound-SNE: comparative alignment of t-SNEs for multiple single-cell omics data visualization.

Autoren: Cess, Colin G Haghverdi, Laleh

Quelle: Bioinformatics; Jul2024, Vol. 40 Issue 7, p1-5, 5p

Schlagwörter: RESEARCH personnel, DATA visualization, GENE expression, DATA analysis, PYTHON programming language

ASAS-NANP symposium: mathematical modeling in animal nutrition—Making sense of big data and machine learning: how open-source code can advance training of animal scientists.

Autoren: Brennan, Jameson R. Menendez, III, Hector M. Ehlert, Krista et al.

Quelle: Journal of Animal Science. Jan2023, Vol. 101 Issue 1, p1-11. 11p. 4 Diagrams, 3 Graphs.

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

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

Quelle: 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.

Autoren: Matysiak, Konrad Hojdis, Aleksandra Szewczuk, Magdalena

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

An extensive study of the effects of different deep learning models on code vulnerability detection in Python code.

Autoren: Wang, Rongcun Xu, Senlei Ji, Xingyu et al.

Quelle: Automated Software Engineering; Jun2024, Vol. 31 Issue 1, p1-35, 35p

Programmed differently? Testing for gender differences in Python programming style and quality on GitHub.

Autoren: Brooke, Siân

Quelle: Journal of Computer-Mediated Communication; Jan2024, Vol. 29 Issue 1, p1-13, 13p

Schlagwörter: PYTHON programming language, PYTHONS, RANDOM forest algorithms, GENDER