• Development and Validation of a Deep Learning Method to Predict Cerebral Palsy From Spontaneous Movements in Infants at High Risk 

      Groos, Daniel; Adde, Lars; Aubert, Sindre Aarnes; Boswell, Lynn; De Regnier, Raye-Ann; Fjørtoft, Toril Larsson; Gaebler-Spira, Deborah; Haukeland, Andreas; Loennecken, Marianne; Msall, Michael; Moinichen, Unn Inger; Pascal, Aurelie; Peyton, Colleen; Ramampiaro, Heri; Schreiber, Michael D.; Silberg, Inger Elisabeth; Songstad, Nils Thomas; Thomas, Niranjan; van den Broeck, Christine; Øberg, Gunn Kristin; Ihlen, Espen Alexander F.; Støen, Ragnhild (Peer reviewed; Journal article, 2022)
      Importance Early identification of cerebral palsy (CP) is important for early intervention, yet expert-based assessments do not permit widespread use, and conventional machine learning alternatives lack validity. Objective ...
    • In-Motion-App for remote General Movement Assessment: a multi-site observational study 

      Adde, Lars; Brown, Annemette; van den Broeck, Christine; DeCoen, Kris; Eriksen, Beate Horsberg; Fjørtoft, Toril Larsson; Groos, Daniel; Ihlen, Espen Alexander F.; Osland, Siril; Pascal, Aurelie; Paulsen, Henriette; Skog, Ole-Morten; Sivertsen, Wiebke; Støen, Ragnhild (Peer reviewed; Journal article, 2021)
      Objectives: To determine whether videos taken by parents of their infants' spontaneous movements were in accordance with required standards in the In-Motion-App, and whether the videos could be remotely scored by a trained ...