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April 24, 2026Computer Methods and Programs in BiomedicineOpen Access

Few-Shot Learning for surgical phase recognition: Performance and generalization in Cholecystectomy

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Authors

FBFlakë BajraktariRARobert AsmußenGGGiuliano A. Giacoppo

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Overview

Demonstrates few-shot learning enhances surgical phase recognition accuracy in low-data environments, indicating a promising approach for surgical assistance systems.

Key Points

  • The aim is to investigate the effectiveness of few-shot learning for recognizing surgical phases with minimal annotated data.
  • Developed a transformer-based few-shot learning model for surgical phase recognition on the Cholec80 dataset.
  • Evaluated performance across three experimental splits to assess generalization in different conditions.
  • Trained the model on minimal annotated examples to test its effectiveness under data-limited contexts.
  • Achieved test accuracies of 89.0%, 75.4%, and 49.1% across three experimental splits.
  • Demonstrated that the model remains effective with limited annotated data, emphasizing data efficiency.
  • Found that domain-specific training significantly enhances accuracy for surgical phase recognition.

Cite This Study

Bajraktari et al. (2026) studied this question.

synapsesocial.com/papers/69eb0899553a5433e34b38c4https://doi.org/10.1016/j.cmpb.2026.109386
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Surgical Phase Recognition in Laparoscopic Cholecystectomy Using Artificial Intelligence2026
  2. 2Automated surgical phase recognition and analysis in single-incision laparoscopic cholecystectomy using artificial intelligence2026
  3. 3Comparative Validation of Machine Learning Algorithms for Surgical Workflow and Skill Analysis with the HeiChole Benchmark2021 · 6 citations
  4. 4Thoracic Surgery Video Analysis for Surgical Phase Recognition2024
  5. 5Speech-Based Surgical Phase Recognition for Non-Intrusive Surgical Skills’ Assessment in Educational Contexts2021 · 25 citations