International multicenter validation of AI-driven ultrasound detection of ovarian cancer

Ovarian lesions are common and often incidentally detected. A critical shortage of expert ultrasound examiners has raised concerns of unnecessary interventions and delayed cancer diagnoses. Deep learning has shown promising results in the detection of ovarian cancer in ultrasound images; however, external validation is lacking. In this international multicenter retrospective study, we developed and validated transformer-based neural network models using a comprehensive dataset of 17,119 ultrasound images from 3,652 patients across 20 centers in eight countries. Using a leave-one-center-out cross-validation scheme, for each center in turn, we trained a model using data from the remaining centers. The models…

• C
  Cancerfonden
• KI
  Karolinska Institutet
• KO
  Knut och Alice Wallenbergs Stiftelse
• V
  Vetenskapsrådet

  Award: 2020-01702
• S
  Samsung