The Surgical Data Science Initiative was initialized by the 1st international workshop on Surgical Data Science organized in Heidelberg, Germany, in June 2016. Key results of this first workshop were a common definition of the field of surgical data science [1] as well as two white papers [1, 2] that identify, present and discuss key initiatives, potential standards, new results, and challenges in the context of surgical data science.

The second edition of the workshop took place on June 17th 2019 and was associated with the International Congress on Computer Assisted Radiology and Surgery (CARS) 2019. It focused on the following topics:

PART 1: OR2020 – Where do we stand? We revisited the document produced 15 years ago by Cleary et al. [3], investigated where we stand, what has hindered us to achieve some of the things envisioned and what are new trends that have not been considered at that time.

PART 2: Surgical Data Science key initiatives: Representatives of key international Surgical Data Science Initiatives gave presentations on the state of the art in the field.

PART 3: Industrial perspectives: Key players from industry shared the perspectives with the long-term goal to develop joint strategies towards efficient research-industry collaboration in the context of surgical data science.

PART 4: Towards Surgical Data Science success stories: Based on the input from the invited speakers as well as the results of the poll performed as part of the registration to the workshop we organized an interactive session with all workshop participants in which we discussed strategies to move the field forward.

The board of the workshop comprised leading clinical and technical experts from the field of surgical data science. Registration to the workshop was free. Industry sponsorship covered the catering.

The article resulting from this workshop is published on arXiv [4].

References:

[1] Lena Maier-Hein, Swaroop S. Vedula, Stefanie Speidel, Nassir Navab, Ron Kikinis, Adrian Park, Matthias Eisenmann, Hubertus Feussner, Germain Forestier, Stamatia Giannarou, Makoto Hashizume, Darko Katic, Hannes Kenngott, Michael Kranzfelder, Anand Malpani, Keno März, Thomas Neumuth, Nicolas Padoy, Carla Pugh, Nicolai Schoch, Danail Stoyanov, Russell Taylor, Martin Wagner, Gregory D. Hager and Pierre Jannin. Surgical data science for next-generation interventions. Nature Biomedical Engineering 1(9), 691 (2017). DOI 10.1038/s41551-017-0132-7

[2] 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 Park, Carla Pugh, Nicolai Schoch, Danail Stoyanov, Russell Taylor, Martin Wagner, S. Swaroop Vedula, Pierre Jannin, Stefanie Speidel. Surgical data science: A consensus perspective, arXiv:1806.03184 2018

[3] Kevin Cleary, Kinsella Audrey, Seong K. Mun. OR 2020 workshop report: Operating room of the future. International Congress Series, 1281: 832-838, Elsevier, 2005.

[4] Lena Maier-Hein, Matthias Eisenmann, Duygu Sarikaya, Keno März, Toby Collins, Anand Malpani, Johannes Fallert, Hubertus Feussner, Stamatia Giannarou, Pietro Mascagni, Hirenkumar Nakawala, Adrian Park, Carla Pugh, Danail Stoyanov, Swaroop S. Vedula, Beat Peter Müller, Kevin Cleary, Gabor Fichtinger, Germain Forestier, Bernard Gibaud, Teodor Grantcharov, Makoto Hashizume, Hannes Kenngott, Ron Kikinis, Lars Mündermann, Nassir Navab, Sinan Onogur, Raphael Sznitman, Russell Taylor, Minu Dietlinde Tizabi, Martin Wagner, Gregory D. Hager, Thomas Neumuth, Nicolas Padoy, Pierre Jannin, Stefanie Speidel. Surgical Data Science — from Concepts to Clinical Translation, arXiv:2011.02284