Prediction of segmental motor outcomes in traumatic spinal cord injury: Advances beyond sum scores.
Sarah C BrüningkLucie BourguignonLouis P Lukasnull nullDoris MaierRainer AbelNorbert WeidnerRüdiger RuppFred GeislerJohn L K KramerJames GuestArmin CurtCatherine R JutzelerPublished in: Experimental neurology (2024)
Our approach is the first to provide predictions across all motor segments independent of the level and severity of SCI. We provide a machine learning concept that is highly interpretable, i.e. the prediction formation process is transparent, that has been validated across European and American data sets, and provides reliable and validated algorithms to incorporate external control data to increase sensitivity and feasibility of multinational clinical trials.