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Published 20 Sep 2024

Tackling Silicosis with AI in Zambia

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Summary  
Listen to Dr. Shibu Vijayan chat with Fwasa Singogo, the National Coordinator of the Ministry of Health in Zambia. They envision incorporating Artificial Intelligence into the mandatory health checkup for mining workers in the country. The conversation highlights the advantages of using AI to simultaneously check for multiple diseases during diagnosis. This can significantly enhance early detection, reduce costs, and save time by speeding up the diagnosis process. Additionally, incorporating this AI tool to diagnose both tuberculosis and silicosis aligns with the WHO's efforts to combat TB, making the approach more cost-effective. 
Key Points 
Where AI could help in Zambia: Diagnosis is the first step for treating a disease. Zambia has institutions to check for TB and other lung diseases for any citizen who intends to work in the mines or is working in it. The limited number of institutions in the country can’t handle the overload. Miners working in the mines can be checked for early identification of Silicosis with the help of AI integration. 
Role of Artificial Intelligence: AI can provide confidence to the doctor in confirming a suspicion. The WHO has been pushing to adopt AI for diagnosis. In many cases, AI has helped doctors from misdiagnosing.  Artificial Intelligence can help in flagging potential threats and provide faster diagnosis for the Minning workers in Zambia while the lung health checkup is being done. 
TB and silicosis: TB is our primary concern. Silicosis is the next major challenge for the country of Zambia. For a country with a significant portion of its population engaged in mining. We are finding ways to ride the wave to clear TB which the WHO leads. If that same AI tool can be integrated with diagnosing silicosis too, that will reduce the cost significantly. 
The challenge to integrate AI while Screening Mining workers: Cost is a major factor for the state. Zambia mandates health checkups for all individuals working in or intending to work in mines. Silicosis among workers is a major concern along with TB. The world is funding for eradicating TB. If the AI tools being used for TB detection could simultaneously diagnose silicosis, the costs can be managed more effectively, addressing both major health concerns among mining workers in our country of Zambia. 
Conclusion 
We can use Artificial Intelligence as a cost-effective tool for validation and effective diagnosis. The campaign by WHO to eradicate TB can go hand in hand with other major issues that the country of Zambia faces, like undiagnosed silicosis. TB is a major concern globally and AI has a significant role to play in it. The same tool can also be integrated with diagnosing another issue like silicosis while checking for TB.  AI in health diagnosis can be used cost-effectively by detecting multiple issues. 

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