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Surgical Data Science: A Consensus Perspective

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arxiv 1806.03184 v1 pith:6OXV2QMG submitted 2018-06-08 cs.CY

classification cs.CY
keywords datasciencesurgicalopenfieldpotentialpublicworkshop
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 1 Pith paper

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  1. SurgX: Neuron-Concept Association for Explainable Surgical Phase Recognition

    cs.CV 2025-07 conditional novelty 5.0 of 10

    SurgX associates neurons in surgical phase recognition models with surgical concepts and uses the concepts of high-contribution neurons to explain predictions on Cholec80.

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