Tuberculosis (TB) continues to be one of the top ten leading causes of death worldwide, with more than 1.3 million reported deaths in 2020. The emergence and spread of drug-resistant forms of the disease have complicated the control of TB in many settings. Adding to the challenge is the fact that treating drug-resistant TB is difficult (the success rate was 57% in 2019), prolonged (treatment can take 9-20 months), and multifaceted (treatment often requires multiple antibiotics that cause severe side effects).
Machine learning model helps identify resistance to key antibiotics for treating tuberculosis
Tuberculosis (TB) continues to be one of the top ten leading causes of death worldwide, with more than 1.3 million reported deaths in 2020. The emergence and spread of drug-resistant forms of the disease have complicated the control of TB in many settings. Adding to the challenge is the fact that treating drug-resistant TB is difficult (the success rate was 57% in 2019), prolonged (treatment can take 9-20 months), and multifaceted (treatment often requires multiple antibiotics that cause severe side effects).