output
20162026
most citedSurgical Data Science: Enabling Next-Generation Surgery

578 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing 2021Show all

7 papers · 1 filter

cs.LG2021★ 173 cited

MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation

Alexandros Karargyris, Renato Umeton, Micah J. Sheller +39

Medical AI has tremendous potential to advance healthcare by supporting the evidence-based practice of medicine, personalizing patient treatment, reducing costs, and improving prov…

cs.CV2021★ 210 cited

Rendezvous: Attention Mechanisms for the Recognition of Surgical Action Triplets in Endoscopic Videos

Chinedu Innocent Nwoye, Tong Yu, Cristians Gonzalez +5

Out of all existing frameworks for surgical workflow analysis in endoscopic videos, action triplet recognition stands out as the only one aiming to provide truly fine-grained and c…

q-bio.TO2021★ 5 cited

Intraoperative time out to promote the implementation of the critical view of safety in laparoscopic cholecystectomy: a video-based assessment of 343 procedures

Pietro Mascagni, Maria Rita Rodriguez-Luna, Takeshi Urade +7

Background: The critical view of safety (CVS) is poorly adopted in surgical practices although it is ubiquitously recommended to prevent major bile duct injuries during laparoscopi…

physics.med-ph2021★ 8 cited

Influence of portal vein occlusion on portal flow and liver elasticity in an animal model

Simon Chatelin, Raoul Pop, Céline Giraudeau +5

Hepatic fibrosis causes an increase in liver stiffness, a parameter measured by elastography and widely used as a diagnosis method. The concomitant presence of portal vein thrombos…

cs.LG2021★ 38 cited

GaNDLF: A Generally Nuanced Deep Learning Framework for Scalable End-to-End Clinical Workflows in Medical Imaging

Sarthak Pati, Siddhesh P. Thakur, İbrahim Ethem Hamamcı +39

Deep Learning (DL) has the potential to optimize machine learning in both the scientific and clinical communities. However, greater expertise is required to develop DL algorithms,…

cs.RO2021★ 28 cited

A Kinematic Bottleneck Approach For Pose Regression of Flexible Surgical Instruments directly from Images

Luca Sestini, Benoit Rosa, Elena De Momi +2

3-D pose estimation of instruments is a crucial step towards automatic scene understanding in robotic minimally invasive surgery. Although robotic systems can potentially directly…

cs.CV2021★ 10 cited

Multi-Task Temporal Convolutional Networks for Joint Recognition of Surgical Phases and Steps in Gastric Bypass Procedures

Sanat Ramesh, Diego Dall'Alba, Cristians Gonzalez +6

Purpose: Automatic segmentation and classification of surgical activity is crucial for providing advanced support in computer-assisted interventions and autonomous functionalities…