Decentralized, privacy-preserving surgical video analysis with Swarm Learning.

ABSTRACT:

Background

Progress in artificial intelligence-based analysis of surgical videos has been constrained by reliance on manual frame-level annotations rather than patient-level outcomes. In addition, concerns about data privacy restrict the exchange of laparoscopic video data and, thereby, multicenter collaboration.

Methods

To address these limitations, we developed a pipeline that integrates weakly supervised deep learning with Swarm Learning, a decentralized machine learning approach that enables collaborative model training without data centralization. We evaluate our pipeline using a newly curated dataset of 397 laparoscopic appendectomy recordings from six international surgical centers. We identified optimal modelling configurations (frame sampling rates and model archite

SUBMITTER: Saldanha OL 

PROVIDER: S-EPMC12622056 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature