Quantifying the incremental value of deep learning: Application to lung nodule detection.

Warsavage T Jr, Xing F, Barón AE, Feser WJ, Hirsch E, Miller YE, Malkoski S, Wolf HJ, Wilson DO, Ghosh D

DOI: 10.1371/journal.pone.0231468
Published: 2020
Container: PloS one
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pone.0231468,
  title = {Quantifying the incremental value of deep learning: Application to lung nodule detection.},
  author = {Warsavage T Jr and Xing F and Barón AE and Feser WJ and Hirsch E and Miller YE and Malkoski S and Wolf HJ and Wilson DO and Ghosh D},
  year = {2020},
  journal = {PloS one},
  doi = {10.1371/journal.pone.0231468},
  url = {https://doi.org/10.1371/journal.pone.0231468}
}

RIS

TY  - JOUR
TI  - Quantifying the incremental value of deep learning: Application to lung nodule detection.
AU  - Warsavage T Jr
AU  - Xing F
AU  - Barón AE
AU  - Feser WJ
AU  - Hirsch E
AU  - Miller YE
AU  - Malkoski S
AU  - Wolf HJ
AU  - Wilson DO
AU  - Ghosh D
PY  - 2020
JO  - PloS one
DO  - 10.1371/journal.pone.0231468
UR  - https://doi.org/10.1371/journal.pone.0231468
ER  -

APA

Jr, W. T., F, X., AE, B., WJ, F., E, H., YE, M., S, M., HJ, W., DO, W., & D, G. (2020). Quantifying the incremental value of deep learning: Application to lung nodule detection.. PloS one. https://doi.org/10.1371/journal.pone.0231468

Source records

pubmed · retrieved 2026-11-10T11:08:18.967Z