Machine Learning in Neurooncology Imaging: From Study Request to Diagnosis and Treatment.
AJR Am J Roentgenol. 2019 Jan;212(1):52-56. doi: 10.2214/AJR.18.20328. Epub 2018 Nov 7.
Villanueva-Meyer JE1, Chang P1, Lupo JM1, Hess CP1, Flanders AE2, Kohli M1.
OBJECTIVE: Machine learning has potential to play a key role across a variety of medical imaging applications. This review seeks to elucidate the ways in which machine learning can aid and enhance diagnosis, treatment, and follow-up in neurooncology.
CONCLUSION: Given the rapid pace of development in machine learning over the past several years, a basic proficiency of the key tenets and use cases in the field is critical to assessing potential opportunities and challenges of this exciting new technology.