Towards clinically interpretable machine learning in emergency surgery: feature importance and insights across clinical time points in abdominal pain cases - Top-Institutions - MDSpire

Towards clinically interpretable machine learning in emergency surgery: feature importance and insights across clinical time points in abdominal pain cases

  • By

  • Jonas Henn

  • Simon Hatterscheidt

  • Svetozar Nesic

  • Sebastian Nowak

  • Wolfgang Block

  • Johannes Röttgen

  • Ingo Gräff

  • Jörg C. Kalff

  • Alois M. Sprinkart

  • Andreas Buness

  • Hanno Matthaei

  • June 16, 2026

  • 0 min

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Top Institutions in Surgery

Brief introduction explaining scope and methodology.

  • #1

    tertiary care hospital
    tertiary care hospital

    Unknown, Unknown

    Key Differentiators

    • Emergency Medicine

  • #2

    R Foundation for Statistical Computing
    R Foundation for Statistical Computing

    Unknown, Unknown

    Key Differentiators

    • Statistical Computing

  • #3

    Posit Software
    Posit Software

    Unknown, Unknown

    Key Differentiators

    • Statistical Software

Original Source(s)

Towards clinically interpretable machine learning in emergency surgery: feature importance and insights across clinical time points in abdominal pain cases

  • by Jonas Henn, Simon Hatterscheidt, Svetozar Nesic, Sebastian Nowak, Wolfgang Block, Johannes Röttgen, Ingo Gräff, Jörg C. Kalff, Alois M. Sprinkart, Andreas Buness, Hanno Matthaei

  • June 16, 2026

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