Supervised and semisupervised methods of nematode images classification for drug discovery

We use computer vision to accelerate the discovery of antiparasitic drug candidates. We trained supervised and semi-supervised deep learning models for identifying images in which the natural product extracts being screened as drug candidates have effectively impacted nematode development. We have developed a novel dataset comprising 12,800 images, consisting of 4,640 labeled and 8,160 unlabeled nematode images. We report the performance of a …