Aim:
The primary aim of this study is to develop a robust and accurate auxiliary diagnostic system for breast cancer by integrating machine learning techniques with a hybrid strategy.
Aim:
To develop a predictive model for early detection of childhood malnutrition using survey-based health and nutrition data, and to compare the performance of ensemble and classical machine learning algorithms.
Aim:
The primary aim of this study is to develop a robust and accurate auxiliary diagnostic system for breast cancer by integrating machine learning techniques with a hybrid strategy.