Large Language Models in Oncology: Revolution or Cause for Concern?

Area of Science:

• Artificial Intelligence
• Oncology
• Large Language Models

Background:

• Artificial intelligence (AI) capabilities are rapidly advancing.
• Large language models (LLMs) present both opportunities and challenges.
• The integration of AI in oncology requires careful evaluation.

Purpose of the Study:

• To review the potential applications of LLMs in oncology.
• To identify and discuss the limitations and concerns regarding LLM implementation.
• To provide a comprehensive overview for future integration strategies.

Main Methods:

• Literature review of AI and LLM applications in oncology.
• Analysis of potential benefits in clinical decision-making, education, and research.
• Examination of ethical, data security, and practical barriers.

Main Results:

• LLMs show promise for enhancing oncology clinical decision-making, education, and research.
• Significant challenges include data inaccuracy, data protection, and accountability.
• Addressing these concerns is vital for successful AI adoption.

Conclusions:

• LLMs offer transformative potential for cancer care.
• Proactive management of ethical and practical issues is essential.
• Ongoing dynamic evaluation of AI in oncology is necessary.