Implementation of Clinical Artificial Intelligence in Radiology: Who Decides and How?
Dania Daye, Walter F. Wiggins, Matthew P. Lungren, Tarik K. Alkasab, Nina Kottler, Bibb Allen, Christopher J. Roth, Bernardo C. Bizzo, Kimberly Durniak, James A. Brink, David B. Larson, Keith J. Dreyer, Curtis P. Langlotz
Abstract
As the role of artificial intelligence (AI) in clinical practice evolves, governance structures oversee the implementation, maintenance, and monitoring of clinical AI algorithms to enhance quality, manage resources, and ensure patient safety. In this article, a framework is established for the infrastructure required for clinical AI implementation and presents a road map for governance. The road map answers four key questions: Who decides which tools to implement? What factors should be considered when assessing an application for implementation? How should applications be implemented in clinical practice? Finally, how should tools be monitored and maintained after clinical implementation? Among the many challenges for the implementation of AI in clinical practice, devising flexible governance structures that can quickly adapt to a changing environment will be essential to ensure quality patient care and practice improvement objectives.