Following this puts new work involving it at the top of your briefing, with a note saying why it is there. Links are taken from the source record, never inferred.
A narrative framework review synthesizing evidence on technical difficulty, surgical quality assessment, and AI-enabled audit for minimally invasive D2 lymphadenectomy, proposing guidance for quality measurement and process review.
This is an unpublished methodological preprint proposing a machine learning algorithm for adaptive scheduling in reinforcement learning; it reports experimental validation but lacks peer review and clinician-relevant hard outcomes.