Search Results - (( (state OR stat) python code analysis ) OR ( (statet OR statene) python code analysis ))*

Programming models to support data science workflows

Authors: Ramón-Cortés Vilarrodona, Cristián

Contributors: University/Department: Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors

Thesis Advisors: Badia Sala, Rosa M. (Rosa Maria), Ejarque Artigas, Jorge

Source: TDX (Tesis Doctorals en Xarxa)

Subject Terms: Distributed computing, High-performance computing, Data science pipelines, Task-ba workflows, Dataflows, Containers (Computer sicience), COMPSs, PyCOMPSs, AutoParallel, Docker, Àrees temàtiques de la UPC::Informàtica

File Description: application/pdf

Access URL: http://hdl.handle.net/10803/669728
https://dx.doi.org/10.5821/dissertation-2117-330142

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: *Experimental design, *Quantitative research, Language models, Python programming language, Generative pre-trained transformers, Benchmark problems (Computer science), Code generators

Quantifying cross-language code reuse via function-level clone detection

Authors: Yi Rong Yan Zhou

Source: Journal of King Saud University: Computer and Information Sciences, Vol 37, Iss 10, Pp 1-20 (2025)

Subject Terms: Natural language processing, Code reuse detection, Function-level clone analysis, Java and python source code, Academic plagiarism detection, Electronic computers. Computer science, QA75.5-76.95

File Description: electronic resource

Relation: https://doaj.org/toc/1319-1578; https://doaj.org/toc/2213-1248

Access URL: https://doaj.org/article/0e8d85656442482785bc981b326c25a4

Numerical Analyses of a SAW Gas Sensor in a Non-Steady State

Authors: T. Hejczyk J. Wrotniak P. Powroźnik et al.

Source: International Journal of Electronics and Telecommunications, Vol vol. 71, Iss No 4 (2025)

Subject Terms: gas sensors, numerical modeling, ingebrigtsen’s formula, dmmp, (rr)-p3ht, acoustoelectric analysis (naa), Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Telecommunication, TK5101-6720

File Description: electronic resource

Relation: https://journals.pan.pl/Content/136909/6-5168-Hejczyk_sk.pdf; https://doaj.org/toc/2081-8491; https://doaj.org/toc/2300-1933

Access URL: https://doaj.org/article/c9d170a1144c4d9f86026066ca8dbfea

Smart Compiler Assistant: An AST based Python Code Analysis

Authors: Aneesh, Ch Saumik, Gembali Varun, Kvv et al.

Source: 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT) ; page 1-6

Availability: https://doi.org/10.1109/icccnt61001.2024.10724220
http://xplorestaging.ieee.org/ielx8/10723818/10723316/10724220.pdf?arnumber=10724220

ChatGPT for Univariate Statistics: Validation of AI-Assisted Data Analysis in Healthcare Research.

Authors: Ruta, Michael R Gaidici, Tony Irwin, Chase et al.

Source: Journal of Medical Internet Research. 2025, Vol. 27, p1-9. 9p.

Subject Terms: *Data analysis, *Data management, ChatGPT, Inferential statistics, Medical care research, Statistical software, Univariate analysis, Descriptive statistics

Company/Entity: OpenAI Inc.

CLAVE: A deep learning model for source code authorship verification with contrastive learning and transformer encoders.

Authors: Álvarez-Fidalgo, David Ortin, Francisco

Source: Information Processing & Management. May2025, Vol. 62 Issue 3, pN.PAG-N.PAG. 1p.

Subject Terms: *Transformer models, Language models, Source code, Dispute resolution, Python programming language

User guide for Social Determinants of Health Survey data in the All of Us Research Program.

Authors: Koleck, Theresa A Dreisbach, Caitlin Zhang, Chen et al.

Source: Journal of the American Medical Informatics Association. Dec2024, Vol. 31 Issue 12, p3032-3041. 10p.

Subject Terms: Social determinants of health, Health equity, Research personnel, Sociometry, Source code

A Firm's Operational Risk: Data Set and Empirical Evidence.

Authors: Astvansh, Vivek Simpson, Joseph J.

Source: Manufacturing & Service Operations Management (M&SOM). Jan/Feb2026, Vol. 28 Issue 1, p326-341. 16p.

Subject Terms: *OPERATIONAL risk, *TRANSFORMER models, *STAKEHOLDER theory, *LEGAL liability, *FINANCIAL disclosure, *EMPIRICAL research, NUMERICAL analysis

Geographic Terms: UNITED States

All of whom? Limitations encountered using All of Us Researcher Workbench in a Primary Care residents secondary data analysis research training block.

Authors: LaPolla, Fred Willie Zametkin Grossi, Marco Barber Chen, Sharon et al.

Source: Journal of the American Medical Informatics Association. Dec2024, Vol. 31 Issue 12, p3008-3012. 5p.

Subject Terms: Secondary analysis, Graduate medical education, Research personnel, Residents (Medicine), Research questions

Risk Model for Metastasis Detection of Neuroblastoma (NB)

Authors: Shenzhen Children's Hospital The Children's Hospital of Zhejiang University School of Medicine Juan Ma, Associate Chief Physician of the Clinical Laboratory Department

Contributors: Shenzhen Children's Hospital The Children's Hospital of Zhejiang University School of Medicine Juan Ma, Associate Chief Physician of the Clinical Laboratory Department

Source: Bone Marrow Cytology-based Artificial Intelligence Model for Detection and Prognosis of Neuroblastoma

DeVAIC: A tool for security assessment of AI-generated code.

Authors: Cotroneo, Domenico De Luca, Roberta Liguori, Pietro

Source: Information & Software Technology. Jan2025, Vol. 177, pN.PAG-N.PAG. 1p.

Subject Terms: *COMPUTER software development, *ARTIFICIAL intelligence, *SECURITY management, CODE generators, 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

Effectiveness of Weight Loss Methods on Lifespan for Metabolic Syndrome

Authors: Nazarbayev University School of Medicine Nazarbayev University Astana Medical University et al.

Contributors: Nazarbayev University School of Medicine Nazarbayev University Astana Medical University et al.

Source: Effectiveness of Pharmacologic, Surgical, and Dietetic Weight Loss Methods on Lifespan in Patients With Metabolic Syndrome: a Comparative Clinical Trial

HABiC: an algorithm based on the exact computation of the Kantorovich-Rubinstein optimizer for binary classification in transcriptomics.

Authors: Cordier, Chiara Jézéquel, Pascal Campone, Mario et al.

Source: Bioinformatics. Jun2025, Vol. 41 Issue 6, p1-13. 13p.

Subject Terms: *PREDICTION algorithms, *TRANSCRIPTOMES, *DEGREES of freedom, *INDIVIDUALIZED medicine, *MACHINE learning

Travel times and distances to health services in Australia

Authors: Michaela Filipcikova Louisa Jorm Sebastiano Barbieri

Source: Scientific Data, Vol 13, Iss 1, Pp 1-6 (2025)

Subject Terms: Science

File Description: electronic resource

Relation: https://doaj.org/toc/2052-4463

Access URL: https://doaj.org/article/3f04c331bd41458c8c42e566f2961448

ORCmKit: an open-source library for organic Rankine cycle modelling and analysis

Authors: Dickes, Rémi Ziviani, Davide van den Broek, Martjin et al.

Contributors: Dickes, Rémi Ziviani, Davide van den Broek, Martjin et al.

Source: Proceedings of ECOS 2016 (2016-06-20); ECOS 2016 - 29th international conference on Efficiency, Cost, Optimisation, Simulation and Environmental Impact of Energy Systems, Portoroz, Slovenia [SI], du 19 juin 2016 au 23 juiin 2016

Subject Terms: ORC, ORCmKit, Modelling, EES, Matlab, Python, simulation, off-design, sizing, Engineering, computing & technology, Energy, Ingénierie, informatique & technologie, Energie

Access URL: https://orbi.uliege.be/handle/2268/198722

Enhancing genome-scale metabolic models with kinetic data: resolving growth and citramalate production trade-offs in Escherichia coli.

Authors: Lázaro, Jorge Wongprommoon, Arin Júlvez, Jorge et al.

Source: Bioinformatics Advances. 2025, Vol. 5 Issue 1, p1-11. 11p.

Subject Terms: *ESCHERICHIA coli, *METABOLIC models, *CHEMICAL kinetics, *METABOLIC flux analysis, *MATHEMATICAL programming

CDL Validation Study

Authors: University Clinic for Ophthalmology and Optometry- Salzburg

Source: Safety and Feasibility of the Cornea DomeLens Ocular Surface Imaging System
Ang M, Cai Y, MacPhee B, Sim DA, Keane PA, Sng CC, Egan CA, Tufail A, Larkin DF, Wilkins MR. Optical coherence tomography angiography and indocyanine green angiography for corneal vascularisation. Br J Ophthalmol. 2016 Nov;100(11):1557-1563. doi: 10.1136/bjophthalmol-2015-307706. Epub 2016 Jan 28.
Steger B, Romano V, Kaye SB. Corneal Indocyanine Green Angiography to Guide Medical and Surgical Management of Corneal Neovascularization. Cornea. 2016 Jan;35(1):41-5. doi: 10.1097/ICO.0000000000000683.
McMonnies CW, Chapman-Davies A. Assessment of conjunctival hyperemia in contact lens wearers. Part I. Am J Optom Physiol Opt. 1987 Apr;64(4):246-50. doi: 10.1097/00006324-198704000-00003.
Bron AJ, Evans VE, Smith JA. Grading of corneal and conjunctival staining in the context of other dry eye tests. Cornea. 2003 Oct;22(7):640-50. doi: 10.1097/00003226-200310000-00008.
Guthoff RF, Baudouin C, Stave J. Atlas of Confocal Laser Scanning In-Vivo Microscopy in Ophthalmology. Springer; 2007
Krachmer JH, Mannis MJ, Holland EJ. Cornea. In: Vol I. 3rd Edition. Mosby Elsevier; 2011.
Steger B, Romano V, Jesacher A, et al. Ocular Surface Photography 2.0 -Curved Object Plane For Corneal Imaging. Appl Opt. in press 2017
Efron N. Grading scales for contact lens complications. Ophthalmic Physiol Opt. 1998 Mar;18(2):182-6. doi: 10.1016/s0275-5408(97)00066-5.

Quantifying the nuclear localization of fluorescently tagged proteins.

Authors: Hurbain, Julien Wolde, Pieter Rein ten Swain, Peter S

Source: Bioinformatics Advances. 2025, Vol. 5 Issue 1, p1-8. 8p.

Subject Terms: *CONVOLUTIONAL neural networks, *MACHINE learning, *CELLULAR signal transduction, *IMAGE processing, *FLUORESCENT proteins, *CELL analysis