Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists

BACKGROUND: Chest radiograph interpretation is critical for the detection of thoracic diseases, including tuberculosis and lung cancer, which affect millions of people worldwide each year. This time-consuming task typically requires expert radiologists to read the images, leading to fatigue-based di...

पूर्ण विवरण

में बचाया:
ग्रंथसूची विवरण
में प्रकाशित:PLoS Med
मुख्य लेखकों: Rajpurkar, Pranav, Irvin, Jeremy, Ball, Robyn L., Zhu, Kaylie, Yang, Brandon, Mehta, Hershel, Duan, Tony, Ding, Daisy, Bagul, Aarti, Langlotz, Curtis P., Patel, Bhavik N., Yeom, Kristen W., Shpanskaya, Katie, Blankenberg, Francis G., Seekins, Jayne, Amrhein, Timothy J., Mong, David A., Halabi, Safwan S., Zucker, Evan J., Ng, Andrew Y., Lungren, Matthew P.
स्वरूप: Artigo
भाषा:Inglês
प्रकाशित: Public Library of Science 2018
विषय:
Research Article
ऑनलाइन पहुंच:https://ncbi.nlm.nih.gov/pmc/articles/PMC6245676/
https://ncbi.nlm.nih.gov/pubmed/30457988
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pmed.1002686
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