Cost Microscope

Cost-effective microscopes, coupled with artificial intelligence, are revolutionizing disease diagnosis, particularly in resource-limited settings. Current research focuses on developing robust deep learning models, often employing domain adaptation techniques, to accurately identify pathogens like malaria parasites from images captured by these less expensive devices. This work addresses the limitations of both high cost and expertise needed for traditional microscopy, aiming to improve accessibility and accuracy of diagnoses globally. The resulting portable and automated diagnostic tools hold significant promise for improving healthcare in underserved communities.