• Computer Science
  • Published in ArXiv 2019

Genetic Deep Learning for Lung Cancer Screening

@article{Park2019GeneticDL,
  title={Genetic Deep Learning for Lung Cancer Screening},
  author={Hunter Park and Connor Monahan},
  journal={ArXiv},
  year={2019},
  volume={abs/1907.11849}
}
Convolutional neural networks (CNNs) have shown great promise in improving computer aided detection (CADe. [...] Key Method We investigated using a genetic algorithm (GA) to conduct a neural architectural search (NAS) to generate a novel CNN architecture to find early stage lung cancer in chest x-rays (CXR). Using a dataset of over twelve thousand biopsy proven cases of lung cancer, the trained classification model achieved an accuracy of 97.15% with a PPV of 99.88% and a NPV of 94.81%, beating models such as…Expand Abstract

Figures, Tables, and Topics from this paper.

References

Publications referenced by this paper.
SHOWING 1-10 OF 37 REFERENCES

Cancer statistics, 2019.

VIEW 1 EXCERPT

DARTS: Differentiable Architecture Search

VIEW 1 EXCERPT

Evolving Deep Neural Networks

VIEW 1 EXCERPT