What I Learned Building a 97%-Accuracy Tumor Classifier (and Why Augmentation Mattered More Than the Model)

I want to walk through the pipeline decisions including the ones that didn't work because that's the part that's actually useful to AI engineer. I recently published my research in MDPI Technologies journal, a unified deep learning framework for multi-class tumor classification. I designed and built the entire pipeline: the data flow the augmentation strategy model selection, and ablation design. We hit 97% accuracy across 10 classes on independent datasets. Here's how it was actually built,…