ISIC 2018: Skin Lesion Analysis Towards Melanoma 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

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Model Accuracy, Loss, and Training Time
Model Inference