Search Results - ((statc OR stat) OR stati) python code analysis~

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

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

Authors: Dunker, Fabian Mendoza, Emil Reale, Marco

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

Subject Terms: 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.

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.

Python Programming: Numerical Analysis/Machine Learning Series.

Authors: Doskas, Constantinos

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

Subject Terms: PYTHON programming language, NUMERICAL analysis, MACHINE learning

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

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

Authors: Li, Jingmao Xu, Yaqing Ma, Shuangge et al.

Source: Bioinformatics; Sep2025, Vol. 41 Issue 9, p1-9, 9p

Subject Terms: CANCER research, GENOTYPE-environment interaction, DIAGNOSTIC imaging, DEEP learning, EMPIRICAL research, COMPUTER simulation

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.

Automation of Software Code Analysis Using Machine Learning Methods.

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

Source: 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

Authors: Tarek A. Atwan

Resource Type: eBook.

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

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

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

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

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.

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.

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

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

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

Authors: Aklilu, Fasil Ashenafi, Hagos Kassa, Tesfu et al.

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

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

Geographic Terms: Ethiopia

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

Authors: Okoye, Stephanie I. Kim, Minjae Petty, Sara et al.

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