August 15, 2025

Cost-Efficient Early Diagnostic Tool for Lung Cancer: Explainable AI in Clinical Systems.

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A new explainable AI model improves lung cancer diagnosis accuracy, suggesting potential for broader clinical adoption.

The new explainable AI model demonstrates strong diagnostic performance, significantly improving early detection efforts for lung cancer.
Achieving an accuracy of 0.8558 and AUC of 0.8600, the model showcases its reliability in diagnosing lung cancer from routine clinical data.
Using a stacking ensemble of artificial neural network and deep neural network, it enhances predictions by including challenging rare cases.
The results suggest promising scalability, but further training on diverse datasets is needed to fully realize its potential as a diagnostic solution.

Sebastian et al. (2025) studied this question.

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