Health Department Considering AI to Detect TB and Silicosis

Estimated read time 2 min read

By Samkele Mchunu

Johannesburg, South Africa – The Department of Health is exploring the use of Artificial Intelligence (AI) to accelerate the screening and diagnosis of tuberculosis (TB) and silicosis. This innovative approach aims to enhance current diagnostic methods and address testing backlogs, particularly among individuals affected by these diseases in mining areas.

From June 20-22, the Health Department will host a conference bringing together TB experts and stakeholders to discuss the potential of AI in improving the accuracy and efficiency of diagnosing TB and silicosis. The conference, themed “Dust and Infection-Free Lungs: Harnessing Artificial Intelligence for TB and Silicosis,” will also focus on strategies to clear existing testing backlogs.

“This follows the recommendation by the World Health Organization for member states to use computer-aided detection software in order to interpret chest X-rays when screening and triaging for tuberculosis,” said spokesperson Foster Mohale. While traditional radiological methods have been essential in diagnosing TB, Mohale noted their limitations in distinguishing between TB and silicosis due to their similar radiological presentations, as well as the occurrence of silico-tuberculosis.

The World Health Organization (WHO) has emphasized the benefits of using computer-aided software for interpreting chest X-rays, which could significantly enhance screening processes. However, the WHO also cautioned that rapid deployment of AI without thorough understanding could potentially harm patients, underscoring the importance of addressing privacy concerns and preventing the entrenchment of existing issues.

Keynote speaker MJ Petroni, a cyborg anthropologist and futurist at Causeit, highlighted the transformative potential of generative artificial intelligence (GenAI). Speaking at the Dell Technologies Forum at the Kyalami Grand Prix Circuit, Petroni stated, “GenAI allows us to solve problems that previously we were told are too expensive to solve. Whether that’s providing healthcare for everyone or a tutor for every child or student or access to information in every language, we can now do that.”

The Department of Health believes that raising awareness about Computer Aided Detection diagnostic tools is crucial in advancing towards the End TB Goal by 2035. By leveraging AI technology, South Africa hopes to make significant strides in combating TB and silicosis, ensuring more effective and timely diagnosis and treatment for affected populations.

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