DeepBackRib: Deep learning to understand factors associated with readmissions after rib fractures.

Journal: The journal of trauma and acute care surgery
Published Date: Sep 19, 2022

Abstract

BACKGROUND: Deep neural networks yield high predictive performance, yet obscure interpretability limits clinical applicability. We aimed to build an explainable deep neural network that elucidates factors associated with readmissions after rib fractures among nonelderly adults, termed DeepBackRib . We hypothesized that DeepBackRib could accurately predict readmissions and a game theoretic approach to elucidate how predictions are made would facilitate model explainability.

Authors

  • Jeff Choi
    From the Division of General Surgery (J.C., K.M., D.I.H., J.D.F.), Department of Surgery, Department of Biomedical Data Science (J.C.), Stanford University; Program in Epithelial Biology (N.Y.L.), Stanford University School of Medicine; and Department of Computer Science (A.P., K.C.), Stanford University, Stanford, California.
  • Jude Alawa
  • Lakshika Tennakoon
  • Joseph D Forrester

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