Auxiliary Diagnosis of Breast Cancer Based on Machine Learning and Hybrid Strategy

5,500.00
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.

Data-Driven Early Diagnosis of Chronic Kidney Disease: Development and Evaluation of an Explainable AI Model

5,500.00
Aim: Ā Ā Ā Ā Ā  The primary aim of this research is to design, build, and rigorously evaluate an interpretable AI model for

Early Detection of Childhood Malnutrition using Survey Data and Machine Learning Approaches

5,500.00

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.

Toward Improving Breast Cancer Classification Using an Adaptive Voting Ensemble Learning Algorithm

5,500.00
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.