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Large language models and artificial intelligence chatbots in vascular surgery.

Fabien Lareyre1, Bahaa Nasr2, Elise Poggi3

  • 1Department of Vascular Surgery, Hospital of Antibes Juan-les-Pins, France; Université Côte d'Azur, Centre National de la Recherche Scientifique (CNRS), UMR7370, Laboratoire de Physiomédecine Moléculaire (LP2M), Nice, France; Fédération Hospitalo-Universitaire FHU Plan & Go, Nice, France.

Seminars in Vascular Surgery
|September 14, 2024
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Summary
This summary is machine-generated.

Large language models (LLMs) and artificial intelligence (AI) chatbots offer new possibilities in vascular surgery. This review explores their potential applications, limitations, and future directions in healthcare.

Keywords:
Artificial intelligenceChatbotLarge language modelNatural language processingVascular diseaseVascular surgery

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Area of Science:

  • Artificial Intelligence
  • Natural Language Processing
  • Medical Informatics

Background:

  • Natural Language Processing (NLP) is a branch of Artificial Intelligence (AI) focused on analyzing human language.
  • Large Language Models (LLMs) are emerging AI technologies with significant potential in various medical fields.
  • The integration of AI chatbots and virtual assistants in healthcare requires careful consideration of benefits and risks.

Purpose of the Study:

  • To provide a comprehensive overview of potential applications of LLMs and AI chatbots in vascular surgery.
  • To examine the utility of these technologies in clinical practice, research, and education within vascular surgery.
  • To identify current limitations and outline future research directions for AI in vascular surgery.

Main Methods:

  • This study employed a narrative review methodology.
  • Literature search focused on large language models, artificial intelligence, chatbots, and vascular surgery.
  • The review synthesized existing knowledge on AI applications in the medical domain, specifically vascular surgery.

Main Results:

  • LLMs and AI chatbots present diverse applications in vascular surgery, spanning patient care, data analysis, and medical training.
  • Potential benefits include enhanced diagnostic support, personalized treatment planning, and streamlined research processes.
  • Significant challenges remain, including data privacy, algorithmic bias, and the need for robust clinical validation.

Conclusions:

  • LLMs and AI chatbots hold considerable promise for transforming vascular surgery practices.
  • Further research and careful implementation are crucial to overcome current limitations and ensure safe, effective integration.
  • The future of vascular surgery may involve synergistic collaboration between human expertise and advanced AI tools.