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ChatGPT's Performance in Spinal Metastasis Cases-Can We Discuss Our Complex Cases with ChatGPT?

Stephan Heisinger1, Stephan N Salzmann1, Wolfgang Senker2

  • 1Department of Orthopedics and Trauma Surgery, Medical University of Vienna, 1090 Vienna, Austria.

Journal of Clinical Medicine
|January 8, 2025
PubMed
Summary

Artificial intelligence (AI), like ChatGPT-4, shows promise in assisting with spinal metastasis treatment planning, aligning with surgeons on 73% of recommendations. However, its generalized approach requires further refinement for complex cancer care.

Keywords:
ChatGPTdecision makingspinal metastasisspinespine surgery

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Area of Science:

  • Oncology
  • Neurosurgery
  • Medical Informatics

Background:

  • Artificial intelligence (AI), specifically large language models (LLMs) like ChatGPT-4, is increasingly integrated into healthcare.
  • Personalized treatment planning is crucial for cancer patients with spinal metastases.
  • The efficacy of AI in assisting complex clinical decision-making for spinal metastasis remains largely untested.

Purpose of the Study:

  • To evaluate the performance of ChatGPT-4 in treatment planning for spinal metastasis cases.
  • To compare AI-driven recommendations with those of experienced spine surgeons.

Main Methods:

  • Five spinal metastasis cases from literature were selected.
  • ChatGPT-4 and five spine surgeons provided standardized treatment recommendations.
  • Responses were analyzed for agreement, frequency distribution, and rater opinions.

Main Results:

  • ChatGPT-4's recommendations agreed with the majority of human raters in 73% of treatment choices.
  • Moderate to substantial agreement was observed for systemic therapy, pain management, and supportive care.
  • Human rater agreement increased when excluding AI, especially for surgical and palliative care decisions, with noted generalized AI responses.

Conclusions:

  • ChatGPT-4 demonstrates potential in aligning with expert surgeons on specific aspects of spinal metastasis treatment.
  • The AI's generalized recommendations highlight limitations, suggesting a need for training with clinical guidelines.
  • Further research is essential to optimize AI tools for personalized cancer treatment decision-making.