Using a national surgical database to predict complications following posterior lumbar surgery and comparing the area under the curve and F1-score for the assessment of prognostic capability
With spinal surgery rates increasing in North America, models that are able to accurately predict which patients are at greater risk of developing complications are highly warranted. However, the previously published methods which have used large, multi-centre databases to develop their prediction models have relied on the receiver operator characteristics curve with the associated area under the curve (AUC) to assess their model's performance. Recently, it has been found that a precision-recall curve with the associated F1-score could provide a more realistic analysis for these models.
Source: The Spine Journal - Category: Orthopaedics Authors: Zachary DeVries, Eric Locke, Mohamad Hoda, Dita Moravek, Kim Phan, Alexandra Stratton, Stephen Kingwell, Eugene Wai, Philippe Phan Tags: Clinical Study Source Type: research