Malarıa Detectıon System

1. Dataset Source:

Rajaraman, S., Antani, S. K., Poostchi, M., Silamut, K., Hossain, M. A., Maude, R. J., ... & Thoma, G. R. (2018). Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images. PeerJ, 6, e4568. (National Institutes of Health - NIH).

2. Technology Used (Grad-CAM):

Selvaraju, R. R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., & Batra, D. (2017). Grad-CAM: Visual explanations from deep networks via gradient-based localization. Proceedings of the IEEE International Conference on Computer Vision (ICCV), 618-626.

3. Biological Context:

World Health Organization. (2023). World malaria report 2023. Geneva: World Health Organization.