A collaboration between the National Center for Supercomputing Applications (NCSA) at the University of Illinois, Mayo Clinic, and the University of Michigan are introducing a new machine-learning-driven approach to latent tuberculosis infection (LTBI) diagnostics. While leveraging a high throughput detection technology and powerful bioinformatics, this approach aims to reveal multi-marker signatures for LTBI diagnosis and risk stratification.
