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September 10, 2025University of Toronto Medical Journal

When Algorithms Meet Anesthesia: A New Era of Patient Safety

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Authors

ESEkambir Saran

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Overview

Analysis of AI's impact on hemodynamic instability and patient safety in anesthesia settings.

Key Points

  • AI integration in anesthesia enhances patient safety and improves outcomes, reducing human error.
  • Machine learning algorithms can predict risks like difficult intubation and hemodynamic instability.
  • AI-driven systems optimize anesthetic control, enhancing precision and reducing variability.
  • Effective patient care combines AI insights with anesthesiologists' clinical judgment and empathy.

Cite This Study

Ekambir Saran (2025) studied this question.

synapsesocial.com/papers/68c1d24654b1d3bfb60f85bchttps://doi.org/10.33137/utmj.v102i2.45043
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