Suchergebnisse - (( (state OR stat) python code analysis ) OR ( state:ct python code analysis ))

  1. 1

    Percolation theory using Python von Malthe-Sørenssen, Anders

    ISBN: 3031598997, 9783031598999, 3031599004, 9783031599002
    Veröffentlicht: Cham Springer 2024
    “… Readers will learn how to generate, analyze, and comprehend data and models, with detailed theoretical discussions complemented by accessible computer codes …”
    Volltext
    E-Book Buch
  2. 2

    Utilizing the open-source programming language Python to create interactive Quality Assurance dashboards for diagnostic and screening performance in Cytology von Kovács, István, Székely, Tamás, Pogány, Péter, Takács, Szabolcs, Erős, Mónika, Járay, Balázs

    ISSN: 2213-2945, 2213-2945
    Veröffentlicht: United States Elsevier Inc 01.07.2024
    “… As a comprehensive solution, we used the Python programming language to create a dashboard application for screening and diagnostic quality metrics …”
    Volltext
    Journal Article
  3. 3

    An image-based modeling framework for patient-specific computational hemodynamics von Antiga, Luca, Piccinelli, Marina, Botti, Lorenzo, Ene-Iordache, Bogdan, Remuzzi, Andrea, Steinman, David A.

    ISSN: 0140-0118, 1741-0444, 1741-0444
    Veröffentlicht: Berlin/Heidelberg Springer-Verlag 01.11.2008
    Veröffentlicht in Medical & biological engineering & computing (01.11.2008)
    “… The framework takes advantage of the integration of image processing, geometric analysis and mesh generation techniques, with an accent on full automation and high-level interaction …”
    Volltext
    Journal Article
  4. 4

    Bayesian modelling of time series data (BayModTS)—a FAIR workflow to process sparse and highly variable data von Höpfl, Sebastian, Albadry, Mohamed, Dahmen, Uta, Herrmann, Karl-Heinz, Kindler, Eva Marie, König, Matthias, Reichenbach, Jürgen Rainer, Tautenhahn, Hans-Michael, Wei, Weiwei, Zhao, Wan-Ting, Radde, Nicole Erika

    ISSN: 1367-4811, 1367-4803, 1367-4811
    Veröffentlicht: England Oxford University Press 02.05.2024
    Veröffentlicht in Bioinformatics (Oxford, England) (02.05.2024)
    “… Motivation Systems biology aims to better understand living systems through mathematical modelling of experimental and clinical data. A pervasive challenge in …”
    Volltext
    Journal Article
  5. 5

    Comprehensive framework of GPU-accelerated image reconstruction for photoacoustic computed tomography von Wang, Yibing, Li, Changhui

    ISSN: 1083-3668, 1560-2281, 1560-2281
    Veröffentlicht: United States Society of Photo-Optical Instrumentation Engineers 01.06.2024
    Veröffentlicht in Journal of biomedical optics (01.06.2024)
    “… Photoacoustic computed tomography (PACT) is a promising non-invasive imaging technique for both life science and clinical implementations. To achieve fast …”
    Volltext
    Journal Article
  6. 6

    Rapid development of image analysis research tools: Bridging the gap between researcher and clinician with pyOsiriX von Blackledge, Matthew D., Collins, David J., Koh, Dow-Mu, Leach, Martin O.

    ISSN: 0010-4825, 1879-0534, 1879-0534
    Veröffentlicht: United States Elsevier Ltd 01.02.2016
    Veröffentlicht in Computers in biology and medicine (01.02.2016)
    “… We present pyOsiriX, a plugin built for the already popular dicom viewer OsiriX that provides users the ability to extend the functionality of OsiriX through simple Python scripts …”
    Volltext
    Journal Article
  7. 7

    MIScnn: a framework for medical image segmentation with convolutional neural networks and deep learning von Müller, Dominik, Kramer, Frank

    ISSN: 1471-2342, 1471-2342
    Veröffentlicht: London BioMed Central 18.01.2021
    Veröffentlicht in BMC medical imaging (18.01.2021)
    “… analysis, metrics, a library with state-of-the-art deep learning models and model utilization like training, prediction, as well as fully automatic evaluation (e.g. cross-validation …”
    Volltext
    Journal Article
  8. 8

    Statistics Using Python von Campesato, Oswald

    ISBN: 9781683928805, 1683928806
    Veröffentlicht: Berlin Mercury Learning and Information 2024
    “… This book is designed to offer a fast-paced yet thorough introduction to essential statistical concepts using Python code samples, and aims to assist data scientists in their daily endeavors …”
    Volltext
    E-Book
  9. 9

    Decoding the JAK-STAT Axis in Colorectal Cancer with AI-HOPE-JAK-STAT: A Conversational Artificial Intelligence Approach to Clinical–Genomic Integration von Yang, Ei-Wen, Waldrup, Brigette, Velazquez-Villarreal, Enrique

    ISSN: 2072-6694, 2072-6694
    Veröffentlicht: Switzerland MDPI AG 17.07.2025
    Veröffentlicht in Cancers (17.07.2025)
    “… : AI-HOPE-JAK-STAT combines large language models (LLMs), a natural language-to-code engine, and harmonized public CRC datasets from cBioPortal …”
    Volltext
    Journal Article
  10. 10

    Introduction to computational causal inference using reproducible Stata, R, and Python code: A tutorial von Smith, Matthew J., Mansournia, Mohammad A., Maringe, Camille, Zivich, Paul N., Cole, Stephen R., Leyrat, Clémence, Belot, Aurélien, Rachet, Bernard, Luque‐Fernandez, Miguel A.

    ISSN: 0277-6715, 1097-0258, 1097-0258
    Veröffentlicht: England Wiley Subscription Services, Inc 30.01.2022
    Veröffentlicht in Statistics in medicine (30.01.2022)
    “… The main purpose of many medical studies is to estimate the effects of a treatment or exposure on an outcome. However, it is not always possible to randomize …”
    Volltext
    Journal Article
  11. 11

    A General Theorem and Proof for the Identification of Composed CFA Models von Bee, R. Maximilian, Koch, Tobias, Eid, Michael

    ISSN: 0033-3123, 1860-0980, 1860-0980
    Veröffentlicht: New York Springer US 01.12.2023
    Veröffentlicht in Psychometrika (01.12.2023)
    “… Composed CFA models are frequently used in the analysis of multimethod data, longitudinal data, or multidimensional psychometric data …”
    Volltext
    Journal Article
  12. 12

    LiPydomics: A Python Package for Comprehensive Prediction of Lipid Collision Cross Sections and Retention Times and Analysis of Ion Mobility-Mass Spectrometry-Based Lipidomics Data von Ross, Dylan H, Cho, Jang Ho, Zhang, Rutan, Hines, Kelly M, Xu, Libin

    ISSN: 1520-6882, 1520-6882
    Veröffentlicht: United States 17.11.2020
    Veröffentlicht in Analytical chemistry (Washington) (17.11.2020)
    “… Existing solutions for these data analysis challenges (i.e., multivariate statistics and lipid identification …”
    Weitere Angaben
    Journal Article
  13. 13

    Identification of Novel Microcystins Using High-Resolution MS and MSn with Python Code von Baliu-Rodriguez, David, Peraino, Nicholas J, Premathilaka, Sanduni H, Birbeck, Johnna A, Baliu-Rodriguez, Tomás, Westrick, Judy A, Isailovic, Dragan

    ISSN: 1520-5851, 1520-5851
    Veröffentlicht: 01.02.2022
    Veröffentlicht in Environmental science & technology (01.02.2022)
    “… Cyanotoxins called microcystins (MCs) are highly toxic and can be present in drinking water sources. Determining the structure of MCs is paramount because of …”
    Weitere Angaben
    Journal Article
  14. 14

    What R and Python programming languages bring to the table von Aller, Raymond D, Weiner, Hal

    ISSN: 0891-1525
    Veröffentlicht: Northfield College of American Pathologists 01.05.2017
    Veröffentlicht in CAP Today (01.05.2017)
    “… The two most widely used open-source big data analysis tools-R and Python-are proving their mettle in the clinical laboratory …”
    Volltext
    Trade Publication Article
  15. 15

    Enhanced deep learning model for precise nodule localization and recurrence risk prediction following curative-intent surgery for lung cancer von Park, Jihwan, Rho, Mi Jung, Moon, Mi Hyoung

    ISSN: 1932-6203, 1932-6203
    Veröffentlicht: United States Public Library of Science 12.07.2024
    Veröffentlicht in PloS one (12.07.2024)
    “… Identifying patients at high risk of recurrence using preoperative computed tomography (CT) images could enable more aggressive surgical approaches, shorter surveillance intervals, and intensified adjuvant treatments …”
    Volltext
    Journal Article
  16. 16

    Development of an Interactive Code for Quick Data Analyses between STOR-M Tokamak Experimental Plasma Discharges von Nakajima, Masaru, Basu, Debjyoti, Melnikov, Alexander V., McColl, David, Xiao, Chijin

    ISSN: 2073-8994, 2073-8994
    Veröffentlicht: Basel MDPI AG 01.08.2022
    Veröffentlicht in Symmetry (Basel) (01.08.2022)
    “… ) tokamak operation, Ohmic H-mode triggering by the electrode biasing, fueling and momentum injection by Compact Torus (CT …”
    Volltext
    Journal Article
  17. 17

    PyLAT: Python LAMMPS Analysis Tools von Humbert, Michael T, Zhang, Yong, Maginn, Edward J

    ISSN: 1549-960X, 1549-960X
    Veröffentlicht: United States 22.04.2019
    Veröffentlicht in Journal of chemical information and modeling (22.04.2019)
    “… Here we describe a suite of open-source Python-based postprocessing routines we have developed called PyLAT …”
    Weitere Angaben
    Journal Article
  18. 18

    GSEApy: a comprehensive package for performing gene set enrichment analysis in Python von Fang, Zhuoqing, Liu, Xinyuan, Peltz, Gary

    ISSN: 1367-4811, 1367-4803, 1367-4811
    Veröffentlicht: England Oxford University Press 01.01.2023
    Veröffentlicht in Bioinformatics (Oxford, England) (01.01.2023)
    “… Abstract Motivation Gene set enrichment analysis (GSEA) is a commonly used algorithm for characterizing gene expression changes …”
    Volltext
    Journal Article
  19. 19

    xMEN: a modular toolkit for cross-lingual medical entity normalization von Borchert, Florian, Llorca, Ignacio, Roller, Roland, Arnrich, Bert, Schapranow, Matthieu-P

    ISSN: 2574-2531, 2574-2531
    Veröffentlicht: United States Oxford University Press 01.02.2025
    Veröffentlicht in JAMIA open (01.02.2025)
    “… Objective To improve performance of medical entity normalization across many languages, especially when fewer language resources are available compared to …”
    Volltext
    Journal Article
  20. 20

    Pyteomics—a Python Framework for Exploratory Data Analysis and Rapid Software Prototyping in Proteomics von Goloborodko, Anton A., Levitsky, Lev I., Ivanov, Mark V., Gorshkov, Mikhail V.

    ISSN: 1044-0305, 1879-1123, 1879-1123
    Veröffentlicht: New York Springer-Verlag 01.02.2013
    “… Pyteomics is a cross-platform, open-source Python library providing a rich set of tools for MS-based proteomics …”
    Volltext
    Journal Article