A group of researchers at the University College London and Africa Health Research Institute have constructed an application using artificial intelligence, capable of improving diagnoses of HIV among people with low socioeconomic status. First released in the journal Nature Medicine, researchers used deep learning algorithms, a form of artificial intelligence, to build more robust diagnoses of HIV-based tests for South African populants. "Although deep learning algorithms show increasing promise for disease diagnosis, their use with rapid diagnostic tests performed in the field has not been extensively tested. Here we use deep learning to classify images of rapid human immunodeficiency virus (HIV) tests acquired in rural South Africa," Valérian Turbé and fellow research colleagues wrote in their findings. "Using newly developed image capture protocols with the Samsung SM-P585 tablet, 60 fieldworkers routinely collected images of HIV lateral flow tests."