Classification of anatomic patterns of peripheral artery disease with automated machine learning (AutoML).

Journal: Vascular
PMID: 38404043

Abstract

AIM: The aim of this study was to investigate the potential of novel automated machine learning (AutoML) in vascular medicine by developing a discriminative artificial intelligence (AI) model for the classification of anatomical patterns of peripheral artery disease (PAD).

Authors

  • Yury Rusinovich
    Department of Vascular Surgery, University Hospital Leipzig, Leipzig, Germany.
  • Volha Rusinovich
    Institute of Hygiene and Environmental Medicine, University Hospital Leipzig, Germany.
  • Aliaksei Buhayenka
    "Human system" Software and System Engineering Company, Minsk, Belarus.
  • Vitalii Liashko
    Department of Vascular Surgery, Charité University Hospital, Berlin, Germany.
  • Arsen Sabanov
    Department of Vascular Surgery, University Hospital Leipzig, Leipzig, Germany.
  • David J F Holstein
    Department of Vascular Surgery, University Hospital Leipzig, Leipzig, Germany.
  • Samer Aldmour
    Department of Vascular Surgery, University Hospital Leipzig, Leipzig, Germany.
  • Markus Doss
    Department of Vascular Surgery, University Hospital Leipzig, Leipzig, Germany.
  • Daniela Branzan
    Gefäßchirurgie, Universitätsklinikum Leipzig, Leipzig, Deutschland.

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