The fight against cancer, a relentless global health crisis, emphasizes the urgency for
efficient and automated early detection methods. To address this critical need, this review …

Cancer continues to be a primary cause of death worldwide, highlighting the critical need for
early diagnosis methods. Automated, quick, and efficient technologies are critical to this …

The accurate diagnosis of lung cancer using predictive modeling presents significant
challenges, primarily due to the imbalanced nature of clinical datasets where certain …

This analysis investigates the magnetohydrodynamic (MHD) boundary layer flow and heat
transfer characteristics of single-walled carbon nanotubes (SWCNTs) dispersed in …

Prompt diagnosis is crucial globally to save lives, underscoring the urgent need in light of
lung cancer's status as a leading cause of death. While CT scans serve as a primary …

This research aims to conduct a systematic review of feature extraction techniques in
patterned images. A total of 47 journals were analyzed to identify the techniques used, their …

Accurate art authentication is crucial for ensuring correct attribution, cultural preservation,
and financial valuation of artworks. Machine learning tools can significantly complement …

This work proposes a complicated voting ensemble model for exact feature selection using
AdaBoost, Catboost, XGBoost, and LARF (LASSO and Recursive Feature Elimination). This …

In India, lung cancer ranks among the top causes of mortality. The purpose of this study is to
evaluate and compare the accuracy of many machine learning techniques for the …

The paper concentrates on boosting the precision and speed of neural networks for lung
cancer diagnosis through novel optimization methodologies. This study employs Long Short …