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A Hybrid MCDM and Machine Learning Framework for Thalassemia Risk Assessment in Pregnant Women
2
Zitationen
10
Autoren
2025
Jahr
Abstract
The proposed MCDM-machine learning framework demonstrates strong potential for improving thalassemia risk assessment, enabling early detection and informed decision-making in maternal healthcare. The proposed framework should be regarded as a preliminary proof-of-concept system that demonstrates the feasibility of integrating Multi-Criteria Decision-Making (AHP-TOPSIS) with advanced machine learning and explainable-AI techniques for thalassemia assessment. Although the model achieved strong diagnostic performance under nested cross-validation, additional external validation and inclusion of causal predictors are required before clinical deployment.
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