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Issues And Trends In Healthcare Delivery System

The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
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Artificial intelligence-based approaches to augmenting and automating surgical training.

Jasmine Lin1, Ludovica Cella2,3, Mitchell G Goldenberg4

  • 1Department of Urology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.

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|March 12, 2026
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Summary

Artificial intelligence (AI) automates surgical skill assessment and feedback, improving training objectivity and scalability. Current AI models excel at identifying major performance differences and offering basic feedback for surgeons.

Keywords:
artificial intelligencedeep learningmachine learningsurgical assessmentsurgical educationsurgical feedbacksurgical skillsurgical training

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Area of Science:

  • Surgical Education Technology
  • Medical Artificial Intelligence
  • Performance Analytics

Background:

  • Traditional surgical skill assessment methods face limitations in objectivity and scalability.
  • There is a growing need for automated tools to enhance surgical training and provide consistent feedback.

Purpose of the Study:

  • To review recent advancements in artificial intelligence (AI) for surgical performance and training.
  • To explore AI's role in automating surgical skill assessment and feedback.

Main Methods:

  • A systematic literature search was conducted on PubMed for studies from 2015-2025.
  • Keywords included "artificial intelligence," "machine learning," "deep learning," "surgical feedback," "surgical training," and "surgical skill."
  • Emphasis was placed on recent publications focusing on AI for skill assessment and feedback.

Main Results:

  • AI successfully automates surgical skill assessment across disciplines using methods like computer vision and gesture analysis.
  • AI models demonstrate high concordance with human raters in classifying skill levels (novice vs. expert).
  • AI-generated feedback improves surgeon performance metrics, especially for underperformers, and aids in analyzing feedback delivery.

Conclusions:

  • AI shows significant promise for enhancing surgical training by improving the objectivity and scalability of skill assessment and feedback.
  • Current AI can detect substantial performance variations and provide basic feedback.
  • Future research should focus on developing AI for more nuanced skill assessments and detailed, constructive feedback.