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May 20, 20260 citationsOpen Access

The S.A.M. Model: A Framework for Safe, Supervised AI‑Assisted Medicine

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SWsamuel james willoughby

Key Points

  • The aim is to present a framework for integrating AI and robotics in surgeries while ensuring human control and oversight.
  • Developed a safety-first framework called S.A.M. Model for surgical practice.
  • Utilized large-scale virtual simulation and real-time monitoring techniques.
  • Implemented a training pipeline and operational structure for continuous learning.
  • Enhanced safety measures and fault tolerance were achieved with the S.A.M. Model.
  • AI served effectively as a predictive monitor without reducing surgeon authority.
  • The model supports a consistent and high-quality surgical environment.

Abstract

The S.A.M. Model (Supervised Autonomous Medicine) proposes a safety‑first framework for integrating artificial intelligence and robotic instrumentation into surgical practice without removing human oversight. The system combines large‑scale virtual simulation, post‑mortem learning, similarity‑based pattern recognition, and real‑time multi‑layer monitoring to create a fault‑tolerant, surgeon‑supervised medical environment. AI functions exclusively as a predictive monitor, robots provide precision execution, and surgeons retain full authority and responsibility at all times. The model outlines a complete training pipeline, operational structure, safety architecture, and economic rationale for a 24/7, high‑consistency surgical system designed to reduce human error while preserving ethical and clinical governance.

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samuel james willoughby (2026) studied this question.

synapsesocial.com/papers/6a0d5098f03e14405aa9c857https://doi.org/10.5281/zenodo.20268920
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