A Historic Breakthrough

The effects of advanced technology’s emergence have been far-reaching. It has changed the dynamics of human life as the old methodologies and approach get more and more blurry every day. Whether these changes fall more on the positive side or the negative side remains a never-ending debate, but it must be acknowledged that the technology has provided us with answers for some of the biggest questions facing the world. These answers stretch across a variety of spheres, helping us in aiming at a more holistic growth. One of the biggest beneficiaries of technology has been the medical sector. Human body is a complex mechanism, therefore for years people have suffered because there was no credible way to fix their medical issue. Fortunately, technology hasn’t only made general medical research possible, but it has also facilitated the study of specific diseases at a granular level. Once equipped with knowledge about a certain disease, technology has also enabled us to create the perfect treatment for it. Nevertheless, there are still many diseases that we continue to look an answer for, and we might just have made a breakthrough in one of them.

HIV has plagued the human race for a long time now. The nature of this disease and the kind of resources it requires for testing and performing care of a basic level has kept HIV as an uncertain territory even for a highly-accomplished medical sector. However, the new collaborated creation of University College London and Africa Health Research Institute brings hope. By combining their resources they have come up with an AI-driven app that can analyze the lateral flow tests for HIV with just an image. The idea behind this is to make independent interpretation of the tests possible, especially in regions where it’s financially and logistically hard to follow standard procedure. It’s understood by the developers that getting early treatment in HIV can be a game-changer, therefore they have made sure that the app delivers required amount of accuracy in a shortened timeframe.

This latest technology is based on a machine learning algorithm that was trained using 11,000 images of lateral flow tests. Upon comparing the app’s accuracy results with the tests observed by human eye, the developers saw app beating the human assessment by 98.9% to 92.1% of accuracy. This technology is also effective in diagnosing other diseases that use lateral flow tests.

Must Read

Related News