Recent developments in data science in general and machine learning in particular have
transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a …

Objective: To provide an overview of ML models and data streams utilized for automated
surgical phase recognition. Background: Phase recognition identifies different steps and …

… Two RCTs defined treatment goals for arterial hypertension (systolic blood pressure <130
mm Hg). Only 1 study defined treatment goals for dyslipidemia (low-density lipoprotein <100 …

Background Laparoscopic liver surgery is particularly challenging owing to restricted access,
risk of bleeding, and lack of haptic feedback. Navigation systems have the potential to …

Background: ALCAM (activated leucocyte cell adhesion molecule, synonym CD166) is a
cell adhesion molecule, which belongs to the Ig superfamily. Disruption of the ALCAM-…

Purpose Surgical workflow and skill analysis are key technologies for the next generation of
cognitive surgical assistance systems. These systems could increase the safety of the …

Background Bariatric surgery gains attention as a potential treatment for non-alcoholic fatty
liver disease (NAFLD). The present study aimed to evaluate improvement of NAFLD after the …

Image-based tracking of medical instruments is an integral part of surgical data science
applications. Previous research has addressed the tasks of detecting, segmenting and tracking …

Abstract Machine learning algorithms are gaining increasing interest in the context of
computer-assisted interventions. One of the bottlenecks so far, however, has been the availability …

Objective: Surprisingly, 40% to 95% of patients with type 2 diabetes mellitus (T2DM) show
early remission of hyperglycemia after obesity surgery. It is unknown to what extent other …