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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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Paging the Algorithm: Applying the Best Available Human Principle to Graduate Medical Education.

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Summary
This summary is machine-generated.

Artificial intelligence (AI) offers new learning opportunities in graduate medical education (GME). The Best Available Human (BAH) standard guides trainees on responsible AI use, ensuring AI complements, not replaces, human expertise.

Keywords:
Best Available Human standardartificial intelligencegraduate medical educationresponsible AI use

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Area of Science:

  • Medical Education
  • Artificial Intelligence
  • Digital Health

Background:

  • Artificial intelligence (AI) is increasingly used in graduate medical education (GME).
  • Formal training on responsible AI use in GME is limited.
  • Trainees are adopting AI tools informally, necessitating structured guidance.

Purpose of the Study:

  • To propose a framework for the responsible integration of AI in GME.
  • To adapt Ethan Mollick's Best Available Human (BAH) standard for GME.
  • To guide trainees on when AI can responsibly augment learning and patient care.

Main Methods:

  • Applying the BAH standard to GME, considering performance and availability thresholds.
  • Integrating structured verification and faculty review for responsible AI use.
  • Examining AI application in clinical instruction, diagnostic reasoning, and health record composition.

Main Results:

  • The BAH standard provides a flexible rule for trainee AI engagement.
  • AI use is conditioned on availability, performance, and verification in key GME domains.
  • Trainee AI competencies are crucial for mastering the BAH principle.

Conclusions:

  • The BAH principle, with structured oversight, enables responsible AI use in GME.
  • Formal incorporation of AI competencies into GME curricula is recommended.
  • Disciplined and responsible AI use is teachable and feasible in GME training programs.