output
20222026
most citedDevelopment and validation of an interpretable machine learning-based calculator for predicting 5-year weight trajectories after bariatric surgery: a multinational retrospective cohort SOPHIA study

90 citations

researchers with a paper here
collaborating institutions
Showing cs.CVShow all

11 papers · 1 filter

cs.CV2026

GEN-Guard: Correcting Generalization Failures for Deployable Federated Surgical AI

Julia Alekseenko, Pietro Mascagni, AI4SafeChole Consortium +1

Federated Learning (FL) in surgical video AI enables collaborative model training without sharing sensitive data. However, standard evaluation practices - selecting the "best" glob…

cs.CV2025

Endoshare: A Publicly Available, Surgeons-Friendly Solution to De-Identify and Manage Surgical Videos

Lorenzo Arboit, Dennis N. Schneider, Britty Baby +3

Video-based assessment and surgical data science can advance surgical training, research, and quality improvement, yet adoption remains limited by heterogeneous recording formats a…

cs.CV2025

S4M: 4-points to Segment Anything

Adrien Meyer, Lorenzo Arboit, Giuseppe Massimiani +3

Purpose: The Segment Anything Model (SAM) promises to ease the annotation bottleneck in medical segmentation, but overlapping anatomy and blurred boundaries make its point prompts…

cs.CV2025★ 6 cited

Early Operative Difficulty Assessment in Laparoscopic Cholecystectomy via Snapshot-Centric Video Analysis

Saurav Sharma, Maria Vannucci, Leonardo Pestana Legori +6

Purpose: Laparoscopic cholecystectomy (LC) operative difficulty (LCOD) is highly variable and influences outcomes. Despite extensive LC studies in surgical workflow analysis, limit…

cs.CV2024★ 9 cited

Surgical Text-to-Image Generation

Chinedu Innocent Nwoye, Rupak Bose, Kareem Elgohary +5

Acquiring surgical data for research and development is significantly hindered by high annotation costs and practical and ethical constraints. Utilizing synthetically generated ima…

cs.CV2023★ 16 cited

Encoding Surgical Videos as Latent Spatiotemporal Graphs for Object and Anatomy-Driven Reasoning

Aditya Murali, Deepak Alapatt, Pietro Mascagni +5

Recently, spatiotemporal graphs have emerged as a concise and elegant manner of representing video clips in an object-centric fashion, and have shown to be useful for downstream ta…