Opportunities and Challenges in Implementing Large Language Models (LLMs) in Oncology.

Area of Science:

• Oncology
• Artificial Intelligence
• Bioinformatics

Background:

• Large language models (LLMs) and artificial intelligence (AI) are poised to transform cancer care.
• Their integration presents both significant opportunities and challenges in clinical and translational oncology.

Purpose of the Study:

• To explore the potential of LLMs and AI in revolutionizing cancer care.
• To identify the opportunities and challenges associated with their implementation in oncology.

Main Methods:

• Analysis of LLM applications in clinical oncology (pathology, radiology, genomics).
• Evaluation of LLM roles in translational research (single-cell transcriptomics, spatial omics, computational pathology).
• Review of ethical considerations (trust, equity, privacy, transparency, non-maleficence, accountability) and implementation hurdles (hallucination, cost, disparities, regulation).

Main Results:

• LLMs can extract large-scale insights from clinical data and accelerate translational research for precision oncology.
• Ethical concerns and implementation challenges, including hallucination risks and healthcare disparities, require careful management.
• Navigating a complex regulatory landscape is essential for responsible deployment.

Conclusions:

• LLMs and AI hold immense promise for advancing cancer care and research.
• Responsible implementation necessitates rigorous validation, ethical vigilance, and a focus on patient welfare.
• Addressing challenges is key to realizing the full potential of AI in oncology.