Synergizing GAN-Driven Synthetic Data Pipelines with Deep Neural Networks for Enhanced Breast Cancer Diagnosis
GAN-generated synthetic histopathology images augment CNN training to achieve 99.17% accuracy, 100% recall, MCC 0.9801, and ROC-AUC 0.9998 for benign vs. malignant classification.
About the author
This paper is authored by Vanshaj Awasthi, a Full Stack Developer based in Pune, Maharashtra, India, with 17+ peer-reviewed publications across IEEE and Springer in medical AI and deep learning, and two IEEE Best Paper Awards. Bachelor of Technology - Computer Science, Amity University Mumbai.
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