| Literature DB >> 31818381 |
Vidur Mahajan1, Vasantha Kumar Venugopal2, Murali Murugavel2, Harsh Mahajan2.
Abstract
There is a plethora of Artificial Intelligence (AI) tools that are being developed around the world aiming at either speeding up or improving the accuracy of radiologists. It is essential for radiologists to work with the developers of such algorithms to determine true clinical utility and risks associated with these algorithms. We present a framework, called an Algorithmic Audit, for working with the developers of such algorithms to test and improve the performance of the algorithms. The framework includes concepts of true independent validation on data that the algorithm has not seen before, curating datasets for such testing, deep examination of false positives and false negatives (to examine implications of such errors) and real-world deployment and testing of algorithms.Keywords: Accuracy; Artificial Intelligence; Deployment; Testing; Validation
Year: 2020 PMID: 31818381 DOI: 10.1016/j.acra.2019.09.009
Source DB: PubMed Journal: Acad Radiol ISSN: 1076-6332 Impact factor: 3.173