Polynomial-SHAP as a SMOTE alternative in conglomerate neural networks for realistic data augmentation in cardiovascular and breast cancer diagnosis

Polynomial-SHAP as a SMOTE alternative in conglomerate neural networks for realistic data augmentation in cardiovascular and breast cancer diagnosis

Abstract Cardiovascular disease (CVD) and breast cancer (BC) are among the leading causes of mortality worldwide, necessitating accurate and interpretable machine learning (ML) models for early diagnosis. Existing approaches often rely on data augmentation techniques such as SMOTE (Synthetic Minorit...

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Bibliographic Details
Main Authors: Chukwuebuka Joseph Ejiyi, Dongsheng Cai, Francis Ofoma Eze, Makuachukwu Bennedith Ejiyi, Jennifer Ene Idoko, Sarpong Kwadwo Asere, Thomas Ugochukwu Ejiyi
Format: Article
Language:English
Published: SpringerOpen 2025-04-01
Series:Journal of Big Data
Subjects:
Breast cancer (BC)
Cardiovascular disease (CVD)
Class imbalance
Feature interactions
Medical diagnosis
SHAP (Shapley additive Explanations)
Online Access:https://doi.org/10.1186/s40537-025-01152-3
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