The potential of AI in cancer care and research

Abstract

Current applications of artificial intelligence (AI), machine learning, and deep learning in cancer research and clinical care are highly diverse—from aiding radiologists in reading medical images to predicting oncoprotein folding and dynamics. The list of available AI-based tools is growing rapidly and will only continue to expand. With the immense potential for AI to advance cancer research and clinical care, the National Cancer Institute (NCI) has a responsibility to consider and support the development and evaluation of such technologies. NCI's current involvement in AI research spans the spectrum of development, implementation, and assessment. That includes generating large, publicly available, curated datasets; shifting the culture of data sharing; training the next generation of scientists in both AI and cancer sciences; fostering interdisciplinary collaborations; investing in research to improve AI methods and models that are designed specifically for cancer; widening access to computing power; procuring computer architecture for future developments; and assuring AI research and technologies follow ethical principles. In addition to a broad overview of AI applications in cancer research and care, and NCI's ongoing AI-based activities, this Perspective outlines NCI's four priority areas for future investment of cancer-focused AI development.