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feat: integrate real SensiNet mammography model
- Add SensiNet dual-stream architecture (Xception + EfficientNet-B3 with CBAM) - Replace mock inference with real Bayesian MC-Dropout prediction (10 passes) - Add /analyze endpoint with SSRF protection (allowlist + private IP blocking) - Add malignancy_probability to response schema - Add training and data preparation utility scripts - Model weights (131MB .pth) gitignored — must be downloaded separately596aaa1 -
feat: bootstrap mammogram inference API starter
1d745c0