Patients Facing Large Language Models in Oncology: A Narrative Review

Area of Science:

• Oncology
• Artificial Intelligence
• Medical Informatics

Background:

• Large language models (LLMs) represent a significant advancement in artificial intelligence.
• Their application in healthcare is rapidly expanding, particularly in specialized fields like oncology.
• Patients increasingly seek accessible information and support throughout their cancer journey.

Purpose of the Study:

• To review the current applications of LLMs in patient care within the oncologic domain.
• To identify the potential benefits of LLM integration for cancer patients.
• To examine the ethical and regulatory considerations surrounding LLM use in oncology.

Main Methods:

• Systematic literature review of studies on LLMs in oncology.
• Analysis of current LLM applications across the patient journey (education, diagnosis, monitoring, follow-up).
• Evaluation of reported benefits, challenges, and ethical implications.

Main Results:

• LLMs are being utilized for patient education, symptom tracking, and treatment adherence support.
• Potential benefits include personalized information, improved communication, and enhanced patient engagement.
• Significant ethical considerations include data privacy, algorithmic bias, and the need for regulatory frameworks.

Conclusions:

• LLMs hold substantial promise for transforming the oncology patient experience.
• Addressing ethical and regulatory challenges is crucial for responsible and effective implementation.
• Further research is needed to optimize LLM integration into routine oncologic care.