Artificial Intelligence Based Solutions to Combat TB

  • Category
    Science & Technology
  • Published
    10th Sep, 2019

Context

The Health Ministry has signed a Memorandum of Understanding (MoU) with Wadhwani Institute for Artificial Intelligence (AI) to explore the application of Artificial Intelligence technology in its fight against tuberculosis (TB) in 2019. That is why it was in news.

About

  • Revised National TB Programme (RNTCP) aims at adoption of AI technologies for building easy TB combats. RNTCP is the state-run tuberculosis (TB) control initiative of the Government of India.
  • As per the National Strategic Plan 2012–17, the program has a vision of achieving a "TB free India", and aims to achieve Universal Access to TB control services.
  • As part of the collaboration, Wadhwani AI would support the National TB programme by helping it become AI-ready which includes developing, piloting, and deploying AI-based solutions. It would support the programme in vulnerability and hot-spot mapping, modeling novel methods of screening and diagnostics.
  • India plans to end TB by 2025, five years ahead of the Global Sustainable Development targets. Meanwhile, World Health Organization (WHO) stated that countries aiming to reduce their TB burden by 2035.
  • Most of the tests used for early detection of TB are not promising. For example, sputum testing is only 50% accurate and frequently misses the disease in its early stages. Molecular testing – while highly accurate – is too expensive for population screening in most regions. AI is very helpful in detection of TB with accuracy and precision.

How AI-Based solutions can combat TB?

  1. A Promising Solution for Early Detection: More recently, there has been interest in using artificial intelligence (AI) for medical image interpretation. Many affected people arrive at clinics too late with advanced disease or multi-drug resistant TB (MDR-TB), which is difficult to treat and more likely to cause death. One of the key strategies to tackle TB is early diagnosis. Unfortunately, sputum testing is only 50% accurate and frequently misses the disease in its early stages.
  2. AI solutions can be deployed offline: The AI-based solutions to combat TB can be used offline with a low power device which is crucial for remote, low-resource settings.
  3. Low cost accessible AI-based TB Solutions: Home Ministry aims to scale its AI solution to provide low-cost, accessible TB detection to vulnerable populations.
  4. Automated disease detection: With focused investment to scale AI solutions for automated disease detection, millions of currently underserved people can gain access to high quality, affordable health screening. The AI-based solution has the potential to lead to earlier detection and make a tremendous impact in battling TB.
  5. Useful Diagnostic Aid: From reading radiographs to adverse event monitoring, sifting through vast datasets to personalize a patient’s care plan or to customize training materials, AI is going to be a useful aid to combat TB

Significance

AI provides a unique opportunity for the health sector, bringing efficiency, saving resources and bringing accuracy in interpretation and enhancing quality of service delivery. Its use in this sector has an ample scope to improve outcomes, especially in situations where resources are limited, further stated the press statement.

About Tuberculosis (TB)

  • Tuberculosis (TB) is an infectious disease usually caused by Mycobacterium tuberculosis (MTB) Bacteria. Tuberculosis generally affects the lungs, but can also affect other parts of the body.
  • India is the country with the highest burden of TB According to the World Health Organization (WHO) India has close to 27 lakh TB cases every year and 4.23 lakh cases die (2016).
  • National Strategic Plan (NSP) for 2017-2025 has been set up in line with other health sector strategies and global efforts, such as the draft National Health Policy 2015, World Health Organization’s (WHO) End TB Strategy and the Sustainable Development Goals (SDGs) of the United Nations (UN) for TB elimination by 2025.

Diagnostic tests for TB disease include the following:

    • Rapid molecular tests: This tests is used to detect influenza viral RNA or nucleic acids in respiratory specimens with high sensitivity and high specificity. Notably, the detection of influenza viral RNA or nucleic acids by molecular assays does not necessarilyindicate detection of viable virus or on-going influenza viral replication. 
    • Sputum smear microscopy: This technique requires the examination of sputum samples using a microscope to determine the presence of bacteria. In the current case definitions recommended by WHO, one positive result is required for a diagnosis of smear-positive pulmonary TB.
    • Culture-based methods: A culture test involves studying bacteria by growing the bacteria on different substances. This is to find out if particular bacteria are present. In the case of the TB culture test the test is to see if the TB bacteria Mycobacterium tuberculosis, are present.

Drug-Resistant TB

Drug-resistant TB occurs when bacteria become resistant to the drugs used to treat TB. This means that the drug can no longer kill the TB bacteria. XDR-TB involves resistance to the two most powerful anti-TB drugs- isoniazid and rifampicin. This is also known as multidrug-resistance (MDR-TB)

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