According to researchers, diagnostic tools such as Machine Learning and precision medicine could help identify tuberculosis patients with the highest risk of reactivation of the disease.

 Researchers from the University of Michigan in the US have shown that identifying multiple biomarkers can provide a more accurate diagnosis for patients with Latent Tuberculosis Infection (LTBI). said Ryan Bailey, Professor at the varsity, said,   "A multi-array test can provide a more detailed, disease-specific glimpse into patient's infection and likely outcome,"

Eat these foods to boost your metabolism and burn belly fat fast

Researchers said, using a precision medicine approach reveals previously obscured diagnostic signatures and reactivation risk potential," said Bailey. The new diagnostic tools will help identify patients with the highest risk of reactivation and will benefit from therapy.

According to the study, published in Integrative Biology, diagnostic tools will also reduce some of the side effects of overtreatment and can be used in the detection of other diseases like autoimmune diseases and cancer.

Knee pain may give rise to the symptoms of depression

Currently, LTBI is tested through a skin scratch test or a blood test that can identify one biomarker but cannot distinguish between memory immune response, vaccine-initiated response, and non-tuberculous mycobacteria exposure. Five per cent, or less is the possibility of correctly identifying the disease through these tests.