Histopathologic Cancer Detection


I participated in this Kaggle competition to create an algorithm to identify metastatic cancer in small image patches taken from larger digital pathology scans. The data for this competition is a slightly modified version of the PatchCamelyon (PCam) benchmark dataset. I got 65th position from 1157 and is in top 6\%.

I also contributed to write a paper “Semi-Supervised Learning for Cancer Detection of Lymph Node Metastase” that has been accepted in workshop Towards Causal, Explainable and Universal Medical Visual Diagnosis, CVPR 2019


Confusion Matrix (Normalized)Confusion Matrix

Results Transfer Learning


  • Jaiswal, Amit Kumar, Ivan Panshin, Dimitrij Shulkin, Nagender Aneja, and Samuel Abramov. “Semi-supervised learning for cancer detection of lymph node metastases.” arXiv preprint arXiv:1906.09587 (2019).