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How far have we come? Artificial intelligence for chest radiograph interpretation

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dc.contributor.author Kallianos, K,
dc.contributor.author Abuya, J
dc.date.accessioned 2021-03-25T07:36:12Z
dc.date.available 2021-03-25T07:36:12Z
dc.date.issued 2019-01
dc.identifier.uri https://www.researchgate.net/publication/330690552_
dc.identifier.uri http://ir.mu.ac.ke:8080/jspui/handle/123456789/4351
dc.description.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 en_US
dc.language.iso en en_US
dc.publisher EPub en_US
dc.subject Artificial intelligence en_US
dc.subject chest radiograph interpretation en_US
dc.title How far have we come? Artificial intelligence for chest radiograph interpretation en_US
dc.type Article en_US


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