Machine learning technologies in CT-based diagnostics and classification of intracranial hemorrhages.

Journal: Zhurnal voprosy neirokhirurgii imeni N. N. Burdenko
Published Date: Jan 1, 2023

Abstract

This review discusses pooled experience of creation, implementation and effectiveness of machine learning technologies in CT-based diagnosis of intracranial hemorrhages. The authors analyzed 21 original articles between 2015 and 2022 using the following keywords: «intracranial hemorrhage», «machine learning», «deep learning», «artificial intelligence». The review contains general data on basic concepts of machine learning and also considers in more detail such aspects as technical characteristics of data sets used for creation of AI algorithms for certain type of clinical task, their possible impact on effectiveness and clinical experience.

Authors

  • A K Smorchkova
    Moscow Research Practical Clinical Center for Diagnostics and Telemedicine Technologies, Moscow, Russia.
  • A N Khoruzhaya
    Moscow Research Practical Clinical Center for Diagnostics and Telemedicine Technologies, Moscow, 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.
  • A V Petryaikin
    Moscow Research Practical Clinical Center for Diagnostics and Telemedicine Technologies, Moscow, Russia.

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