Proscia announced new research on improving the generalization of an artificial intelligence (AI) classification model with contrastive self-supervised learning. The results, which include a 56.3% increase in melanoma detection sensitivity, will be presented at the Conference on Neural Information Processing Systems (NeurIPS) 2022.
Proscia’s retrospective study “Learning SimCLR Representations for Improving Melanoma Whole Slide Images Classification Model Generalization” was conducted with data from three sites. The study investigated the impact of extended training time and different augmentations on an AI model that leverages the SimCLR framework of contrastive self-supervised learning to classify melanoma cases.
The results show that optimizing these factors can improve the generalization of an AI model trained with data from two sites, demonstrating a 56.3% increase in melanoma detection sensitivity when evaluated on images from the third site. As melanoma is the deadliest form of skin cancer and often challenging to diagnose, the findings illustrate the promise of contrastive self-supervised learning to help lower the misdiagnosis rate.
