Clinical acceptance of software based on artificial intelligence technologies (radiology)

S. P. Morozov; A. V. Vladzymyrskyy; V. G. Klyashtornyy; A. E. Andreychenko; N. S. Kulberg; V. A. Gombolevsky; K. A. Sergunova

Clinical acceptance of software based on artificial intelligence technologies (radiology)

Artificial Intelligence 2020-02-28 v2 Computers and Society

Authors: S. P. Morozov , A. V. Vladzymyrskyy , V. G. Klyashtornyy , A. E. Andreychenko , N. S. Kulberg , V. A. Gombolevsky , K. A. Sergunova

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Abstract

Aim: provide a methodological framework for the process of clinical tests, clinical acceptance, and scientific assessment of algorithms and software based on the artificial intelligence (AI) technologies. Clinical tests are considered as a preparation stage for the software registration as a medical product. The authors propose approaches to evaluate accuracy and efficiency of the AI algorithms for radiology.

Keywords

clinical decision support artificial intelligence medical informatics

Cite

@article{arxiv.1908.00381,
  title  = {Clinical acceptance of software based on artificial intelligence technologies (radiology)},
  author = {S. P. Morozov and A. V. Vladzymyrskyy and V. G. Klyashtornyy and A. E. Andreychenko and N. S. Kulberg and V. A. Gombolevsky and K. A. Sergunova},
  journal= {arXiv preprint arXiv:1908.00381},
  year   = {2020}
}

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Clinical acceptance of software based on artificial intelligence technologies (radiology)

Abstract

Keywords

Cite

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