- Introduced slide-level confidence and threshold. The App will output binary classification result for each slide.
- Now uses different colors to indicate the confidence level for each parasite detection.
NLM Malaria Screener is a diagnostic app that assists users in the diagnosis of malaria and in the monitoring of malaria patients. The app counts infected and uninfected red blood cells in blood smear images captured by the smartphone camera when attached to the eyepiece of a microscope. It uses image analysis and machine learning methods to identify individual cells and discriminates between infected and uninfected cells. The app reports the detected parasitemia to the user and stores it in a patient database, allowing monitoring of patients over time.
NLM Malaria Screener is an R&D project of the Lister Hill National Center of Biomedical Communications, which is a division of the National Library of Medicine (NLM) at the National Institutes of Health (NIH). The app development is in tight collaboration with national and international partners, including Mahidol University (Thailand), University of Oxford (UK), and University of Missouri.
The app is currently in a beta testing phase and ongoing research and development aims at adding more functionality in the future. Organizations and institutes with a vested interest in malaria diagnosis, either for research or field screening, are welcomed to test the beta version and to provide feedback, which would help in the improvement of the app. If interested, please contact us at the email address given in the app, or visit our project webpage https://ceb.nlm.nih.gov/projects/malaria-screener/
