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Ensuring privacy protection in the era of big laparoscopic video data: development and validation of an inside outside discrimination algorithm (IODA).

A SchulzeD TranM T J DaumA KisilenkoL Maier-HeinS SpeidelM DistlerJ WeitzB P Müller-StichS BodenstedtMartin Wagner
Published in: Surgical endoscopy (2023)
IODA is able to discriminate between inside and outside with a high certainty. In particular, only a few outside frames are misclassified as inside and therefore at risk for privacy breach. The anonymized videos can be used for multi-centric development of surgical AI, quality management or educational purposes. In contrast to expensive commercial solutions, IODA is made open source and can be improved by the scientific community.
Keyphrases
  • big data
  • artificial intelligence
  • machine learning
  • health information
  • deep learning
  • mental health
  • healthcare
  • electronic health record
  • robot assisted
  • magnetic resonance imaging