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TG TB: Topic Group on "Tuberculosis"

Scope

This FG-AI4H topic group is dedicated to using artificial intelligence methods for tuberculosis prognostics, diagnosis and prediction.

How to join: Call for topic group participation
Topic description & status report

Management and Contact

Topic driver:

Manjula Singh (ICMR, India)

Secretariat:

tsbfgai4h@itu.int

Activities

E-meetings

All parent group meetings

Participating

Documentation
Mailing list: fgai4h@lists.itu.int
Join the mailing list (ITU account needed):
Experts | Step-by-step
Collaboration site (ITU account needed - instructions)
Templates: Documents | Liaison Statements

Background

Tuberculosis (TB) is a huge problem worldwide with about 50 % of the cases in BRICS countries. With an estimated 2.3 million reported cases in 2011 and an additional 1 million undocumented cases, India has the highest prevalence of TB in the world. Each year 2.8 million cases develop TB and about 1 million cases go unreported or undiagnosed. Solving the TB crisis has been a top public health priority for years. Machine learning (ML) techniques have been used world-wide for improving public health through development of better prognostic, diagnostic and predictive models. There is a need to detect the missed cases by early adoption of Computer Assisted Diagnosis (CAD) systems based on artificial intelligence (AI) technologies for TB detection. This will synergize with the global endeavours to close the gap in TB control.