Text Analysis of Radiology Reports with Signs of Intracranial Hemorrhage on Brain CT Scans Using the Decision Tree Algorithm.

Journal: Sovremennye tekhnologii v meditsine
Published Date: Nov 28, 2022

Abstract

UNLABELLED: is to create, train, and test the algorithm for the analysis of brain CT text reports using a decision tree model to solve the task of simple binary classification of presence/absence of intracranial hemorrhage (ICH) signs.

Authors

  • А N Khoruzhaya
    Junior Researcher, Department of Innovative Technologies; Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, Bldg 1, 24 Petrovka St., Moscow, 127051, Russia.
  • D V Kozlov
    Junior Researcher, Department of Medical Informatics, Radiomics and Radiogenomics; Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, Bldg 1, 24 Petrovka St., Moscow, 127051, Russia.
  • К M Arzamasov
    Head of the Department of Medical Informatics, Radiomics and Radiogenomics; Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, Bldg 1, 24 Petrovka St., Moscow, 127051, Russia.
  • E I Kremneva
    Leading Researcher, Department of Innovative Thechnologies; Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, Bldg 1, 24 Petrovka St., Moscow, 127051, Russia; Senior Researcher; Research Center of Neurology, 80 Volokolamskoye Shosse, Moscow, 125367, Russia.

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