A Practical Guide for AI Algorithm Selection for the Radiology Department.

Journal: Seminars in roentgenology
Published Date:

Abstract

There is a steadily increasing number of artificial intelligence (AI) tools available and cleared for use in clinical radiological practice. Radiologists will increasingly be faced with options provided by other radiologist colleagues, clinician colleagues, vendors, or other professionals for obtaining and deploying AI algorithms in clinical practice. It is important that radiologists are familiar with basic and practical aspects that need to be considered when assessing an AI tool for use in their practice, so that resources are properly allocated and there is an appropriate return on investment through enhancements in patient quality of care, safety, and/or process efficiency. In this review, we will discuss a potential approach for AI software assessment and practical points that should be considered when considering the acquisition and deployment of an AI tool in the radiology department.

Authors

  • Reza Forghani
    Department of Radiology, McGill University Health Centre, 1001 Decarie Blvd, Room C02.5821, Montreal, QC, Canada H4A 3J1; Augmented Intelligence & Precision Health Laboratory (AIPHL), Research Institute of the McGill University Health Centre, Montreal, Canada; Segal Cancer Centre and Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Canada; Gerald Bronfman Department of Oncology, McGill University, Montreal, Canada; and Department of Otolaryngology-Head and Neck Surgery, McGill University, Montreal, Canada.