Surgical data science: A consensus perspective

Lena Maier-Hein, Matthias Eisenmann, Carolin Feldmann, Hubertus Feussner, Germain Forestier, Stamatia Giannarou, Bernard Gibaud, Gregory D. Hager, Makoto Hashizume, Darko Katic, Hannes Kenngott, Ron Kikinis, Michael Kranzfelder, Anand Malpani, Keno März, Beat Müller-Stich, Nassir Navab, Thomas Neumuth, Nicolas Padoy, Adrian ParkCarla Pugh, Nicolai Schoch, Danail Stoyanov, Russell Taylor, Martin Wagner, S. Swaroop Vedula, Pierre Jannin, Stefanie Speidel

Research output: Contribution to journalArticlepeer-review


Surgical data science is a scientific discipline with the objective of improving the quality of interventional healthcare and its value through capturing, organization, analysis, and modeling of data. The goal of the 1st workshop on Surgical Data Science was to bring together researchers working on diverse topics in surgical data science in order to discuss existing challenges, potential standards and new research directions in the field. Inspired by current open space and think tank formats, it was organized in June 2016 in Heidelberg. While the first day of the workshop, which was dominated by interactive sessions, was open to the public, the second day was reserved for a board meeting on which the information gathered on the public day was processed by (1) discussing remaining open issues, (2) deriving a joint definition for surgical data science and (3) proposing potential strategies for advancing the field. This document summarizes the key findings.

Original languageEnglish (US)
JournalUnknown Journal
StatePublished - Jun 8 2018


  • Biomedical Data Science
  • Computer Aided Surgery
  • Computer Assisted Interventions
  • Robotics
  • Surgical Data Science

ASJC Scopus subject areas

  • General

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