| Literature DB >> 30704666 |
K Kallianos1, J Mongan1, S Antani2, T Henry1, A Taylor1, J Abuya3, M Kohli4.
Abstract
Due to recent advances in artificial intelligence, there is renewed interest in automating interpretation of imaging tests. Chest radiographs are particularly interesting due to many factors: relatively inexpensive equipment, importance to public health, commonly performed throughout the world, and deceptively complex taking years to master. This article presents a brief introduction to artificial intelligence, reviews the progress to date in chest radiograph interpretation, and provides a snapshot of the available datasets and algorithms available to chest radiograph researchers. Finally, the limitations of artificial intelligence with respect to interpretation of imaging studies are discussed.Mesh:
Year: 2019 PMID: 30704666 DOI: 10.1016/j.crad.2018.12.015
Source DB: PubMed Journal: Clin Radiol ISSN: 0009-9260 Impact factor: 2.350