Fine-tuned CNNs reach 96 to 98 percent test accuracy on a 57,111-image chest X-ray task, but Grad-CAM and the authors' own analysis show the models rely in part on non-lung artifacts.
A comprehensive analysis of deep learning-based approaches for prediction and prognosis of infectious diseases
1 Pith paper cite this work, alongside 41 external citations. Polarity classification is still indexing.
1
Pith paper citing it
41
external citations · OpenAlex
citation-role summary
background 1
citation-polarity summary
fields
eess.IV 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Chest Disease Detection In X-Ray Images Using Deep Learning Classification Method
Fine-tuned CNNs reach 96 to 98 percent test accuracy on a 57,111-image chest X-ray task, but Grad-CAM and the authors' own analysis show the models rely in part on non-lung artifacts.