Cancer is the most fatal diseases in the world which has highest mortality rate as compared
to other type's human diseases. The most common and dangerous types of cancers are lung …

The use of data-driven high-throughput analytical techniques, which has given rise to
computational oncology, is undisputed. The widespread use of machine learning (ML) and …

Introduction Colorectal cancer (CRC), also known as colorectal cancer, is a significant
disease marked by high fatality rates, ranking as the third leading cause of global mortality …

Simple Summary Accounting for 10% of the new cases in 2020, colorectal cancer (CRC) is
one of the most prevalent cancers worldwide. Unfortunately, CRC is frequently identified at a …

Cancer poses a significant threat to life due to its aggressive nature, high potential for
metastasis, and heterogeneity. Globally, both the men and women are mostly affected by …

Simple Summary This research aims to evaluate the effectiveness of a machine learning
algorithm, XGBoost, in predicting treatment recommendations for patients with …

Simple Summary Cancer treatments often have side effects that may impair patients' quality
of life. Our research aimed to create a predictive tool able to foresee the likelihood of these …

Colon cancer is a prevalent and potentially fatal disease that demands early and accurate
diagnosis for effective treatment. Traditional diagnostic approaches for colon cancer often …

Results: Time from diagnosis, age, tumor size, metastatic status, lymph node involvement,
and treatment type emerged as crucial predictors of survival based on mean decrease GINI …

In this study, we present a novel approach to enhancing the interpretability of medical image
classification by integrating formal concept analysis (FCA) with convolutional neural …