Swarnadip Chatterjee

Achieving transformation-consistent anomaly detection in cytology could revolutionize how we identify malignant cells in rare and heterogeneous datasets.

Forget fully supervised learning: one-class representation learning can now outperform it for detecting extremely rare malignant cells in cytological images, even with witness rates as low as 1%.