Surgical data science for next-generation interventions

By Lena Maier-Hein, S. Vedula, S. Speidel, Nassir Navab, Ron Kikinis, A. Park, M. Eisenmann, Hubertus Feußner, Germain Forestier, S. Giannarou and 15 more. Nature Biomedical Engineering, 2017

522 citations recorded by the source corpus.

Interventional healthcare will evolve from an artisanal craft based on the individual experiences, preferences and traditions of physicians into a discipline that relies on objective decision-making on the basis of large-scale data from heterogeneous sources.

Subfields: Biomedical Engineering, Health Informatics, Surgery

View Paper: https://www.semanticscholar.org/paper/0ec2d4c804dd2b4446e1808dc85b4fe4a27b1766

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Daniel Richard Leff
2. Nassir Navab
3. Gregory Hager
4. Russell H. Taylor
5. Ron Kikinis

In Surgery

1. Gregory Hager
2. Russell H. Taylor

Citations in the corpus

• Surgical data science – from concepts toward clinical translation (2020, background): “The perioperative data is processed to derive information addressing a specific clinical need, where applications may range from prevention and training to interventional diagnosis, treatment assistance and follow-up (Maier-Hein et al., 2017).”