Large language models as decision aids in neuro-oncology: a review of shared decision-making applications

J Cancer Res Clin Oncol. 2024 Mar 19;150(3):139. doi: 10.1007/s00432-024-05673-x.

Abstract

Shared decision-making (SDM) is crucial in neuro-oncology, fostering collaborations between patients and healthcare professionals to navigate treatment options. However, the complexity of neuro-oncological conditions and the cognitive and emotional burdens on patients present significant barriers to achieving effective SDM. This discussion explores the potential of large language models (LLMs) such as OpenAI's ChatGPT and Google's Bard to overcome these barriers, offering a means to enhance patient understanding and engagement in their care. LLMs, by providing accessible, personalized information, could support but not supplant the critical insights of healthcare professionals. The hypothesis suggests that patients, better informed through LLMs, may participate more actively in their treatment choices. Integrating LLMs into neuro-oncology requires navigating ethical considerations, including safeguarding patient data and ensuring informed consent, alongside the judicious use of AI technologies. Future efforts should focus on establishing ethical guidelines, adapting healthcare workflows, promoting patient-oriented research, and developing training programs for clinicians on the use of LLMs. Continuous evaluation of LLM applications will be vital to maintain their effectiveness and alignment with patient needs. Ultimately, this exploration contends that the thoughtful integration of LLMs into SDM processes could significantly enhance patient involvement and strengthen the patient-physician relationship in neuro-oncology care.

Keywords: Ethical considerations; Healthcare integration; Large language models; Neuro-oncology care; Patient engagement; Shared decision making.

Publication types

  • Review

MeSH terms

  • Decision Support Techniques
  • Health Personnel*
  • Humans
  • Informed Consent*
  • Language
  • Patient Participation