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AI in Healthcare

Clinical Decision Support with Large Language Models

Large language models can help summarize context, but safe clinical use demands strong guardrails.

Dr. Sarah AhmedDr. Sarah Ahmed
Apr 6, 2026
8 min read
860 views
Dr. Sarah Ahmed

Dr. Sarah Ahmed

Associate Professor, Department of Biomedical Engineering

University of Toronto, Canada

Dr. Sarah Ahmed's research focuses on medical image analysis, machine learning applications in healthcare, and computer vision.
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Abstract

Large language models offer useful summarization and retrieval support in clinical environments.

1. Introduction

Interest in language-model-driven clinical tools has increased because documentation burden remains high.

2. Potential Use Cases

Drafting summaries and surfacing references are plausible near-term applications.
  • Documentation assistance
  • Clinical summarization
  • Reference retrieval

3. Safety Boundaries

Support tasks must remain clearly separated from autonomous clinical decision-making.

4. Future Directions

Retrieval grounding and tighter governance will shape safer deployment.

5. Conclusion

Language models can be useful when they remain supervised and well-scoped.

References

  1. LLM reference 1
  2. LLM reference 2
  3. LLM reference 3
Tags:LLMClinical Decision SupportSafety
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