Friday, May 03, 2019

Harvard undergrad's AI model helps to predict TB resistance

One of the greatest challenges in treating tuberculosis—the top infectious killer worldwide, according to the World Health Organization (WHO)—is the bacterium's ability to shapeshift rapidly and become resistant to multiple drugs. Identifying resistant strains quickly and choosing the right antibiotics to treat them remains difficult for several reasons, including the bacterium's propensity to grow slowly in the lab, which can delay drug-sensitivity test results by as much as six weeks after initial diagnosis.

* This article was originally published here