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Updated: Jun 28, 2025

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Artificial Intelligence in Cataract Surgery: A Systematic Review.

Simon Müller1, Mohit Jain2, Bhuvan Sachdeva2,3

  • 1University Hospital Bonn, Department of Ophthalmology, Bonn, Germany.

Translational Vision Science & Technology
|April 15, 2024
PubMed
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This summary is machine-generated.

Artificial intelligence (AI) algorithms show promise for analyzing cataract surgery videos, with strong performance in instrument tracking and phase recognition. However, challenges remain in assessing surgical skill and complications due to data limitations and lack of standardized metrics.

Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Cataract surgery video analysis using AI is an emerging field.
  • Assessing the reliability and current applications of AI algorithms is crucial for clinical integration.

Approach:

  • A systematic literature review was conducted on AI algorithms for intra-operative cataract surgery video analysis.
  • Algorithms were compared based on performance metrics, reproducibility, and reliability using a modified MICCAI checklist.

Key Points:

  • Thirty-eight studies were included, focusing on instrument detection/tracking, phase discrimination, and skill/complication prediction.
  • High performance was noted for instrument detection (ROC AUC 0.976-0.998) and phase recognition (ROC AUC 0.773-0.990).
  • Surgical skill and complication recognition remain challenging for AI models.

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Conclusions:

  • AI-based analysis of cataract surgery videos shows significant potential for improving surgical training.
  • Limitations include a lack of public datasets, inconsistent reporting of metrics, and rare external validation.
  • Further standardization and data sharing are needed to advance AI in this domain.