(Хмельницький національний університет, 2018) Radiuk, P.M.; Радюк, П.М.
Convolutional neural networks demonstrate impressive results during medical imaging of lung cancer. It may be
possible to make diagnoses with convolutional neural networks on conventional chest X-rays that are definitively apparent
on subsequently computed tomography and biopsy. Computer vision may reduce the need for further evaluation with invasive
testing or prevent errors of missed diagnoses. Using over twelve thousand images of proven lung cancer from the Prostate,
Lung, Colorectal, and Ovarian dataset, we developed an algorithm to predict the presence or absence of lung cancer. The
classification algorithm has achieved an accuracy of 96.09% with a positive predictive value of 99.11% and a negative
predictive value of 93.25%.