Clinical validation of lightweight CNN architectures for reliable multi-class classification of lung cancer using histopathological imaging techniques | Synapse
March 3, 2026Open Access
Clinical validation of lightweight CNN architectures for reliable multi-class classification of lung cancer using histopathological imaging techniques
Puntos clave
Reliable classification of lung cancer was achieved through lightweight convolutional neural network architectures.
The study found that these CNN architectures reached an accuracy of over 90% in histopathological imaging.
Analysis involved histopathological imaging techniques applied to diverse lung cancer samples.
The findings suggest that lightweight CNNs may enhance clinical decision-making in lung cancer diagnostics.