Stress testing a deep learning algorithm for normal/abnormal classification of Chest X-rays on a spectrum-biased abnormal weighted dataset
Poster Presentation at the European Congress of Radiology, Vienna, 2019
To stress test the performance of a deep learning algorithm on a dataset with spectrum bias against normalcy in chest x-ray normal vs. abnormal classifier.
Methods and Materials
A Deep Learning algorithm consisting of an ensemble of 14 Convolutional Neural Networks and a weighting Fully Connected Network was trained with more than 100,000 Chest
The algorithm correctly classified 237 (78.74%) CXRs with a sensitivity of 83.76% (95% CI - 77.85% to 88.62%) and specificity of 69.23% (95% CI - 59.42% to 77.91%). There were
As compared to the validation results, there is an increment in