AI pioneer’s mission to revolutionize Nigerian healthcare

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Sumedh Vilas Datar

In Nigeria, the issue of healthcare inequity looms large. There are only around four doctors per 10,000 people — for context, Sweden has seven times more. Combined with other problems related to infrastructure and costs, Nigeria suffers thousands of unnecessary deaths every year. However, emerging technologies like machine learning and computer vision offer a beacon of hope, and innovators like Sumedh Vilas Datar have already impacted healthcare in India and are trying to speed up these technologies around the world.

Access to healthcare is a critical issue for many African countries. Child mortality is high in the region, and infectious diseases like malaria and HIV/AIDs loom large. Meanwhile, infrastructure and staff are visibly lacking. Nowhere is this truer than in Nigeria. In overpopulated cities like Lagos and Abuja, hospitals are crowded and resources are stretched, with too many people vying for too few resources. Rural areas don’t fare much better — there’s often a complete absence of essential medical services.

As if the poor infrastructure and limited resources didn’t make it difficult enough to access treatment, costs are often prohibitively high. Nigeria’s National Health Insurance Scheme (NHIS) covers less than 5% of the population.

The situation is further compounded by so-called brain drain: the phenomenon of skilled professionals like doctors and nurses choosing to work abroad for better opportunities. Sadly, the outcome is high mortality rates from preventable diseases like malaria, HIV/AIDS and tuberculosis. However, innovations may be about to change the country’s direction.

Technological interventions like deep learning and computer vision — both subfields of artificial intelligence — could revolutionize healthcare. Deep learning algorithms can analyze complex medical data with high accuracy — allowing for quicker, more accurate, and more affordable diagnoses. Meanwhile, computer vision enables machines to interpret visual data, allowing algorithms to make sense of X-rays or other medical images.

By reducing reliance on healthcare workers, these technologies could make healthcare services more widely available.

Sumedh Vilas Datar stands out as a pioneer in these fields, with his work having significant implications for accessible healthcare. We recognized his work after he became a Fellow of The Institute of Data Scientists and Analysts, receiving the highest grade honor for the society in Nigeria for his extraordinary work in the healthcare, retail industry and promoting data literacy around the world.

After watching medical professionals struggling to pinpoint cancerous regions accurately using traditional methods, Datar decided to use deep learning techniques to find a better solution. He played a critical role in coming up with an innovative algorithm. He used a proprietary variant of transfer learning to automate image analysis, using minimal data from the manual process to build their algorithm. Not only was he able to create an algorithm successfully, but it ended up being 20-25% more accurate at diagnosing than the traditional methods and received much faster results.

This isn’t the only step Datar has taken to improve healthcare. He’s also participated in research projects to find cancerous regions in the mouth using biomedical image processing, and used machine algorithms to identify polyps and ulcers from endoscopic images. Thanks to his contributions, Datar has garnered various patents and accolades. Most notably, he received fellowship awards from The Institute of Data Scientists and Analysts, and the British Computing Society.

Unequal access to healthcare is a complex issue, and there’s no quick fix to solve it overnight. However, technological innovations like those pioneered by Datar could have far-reaching impacts — especially in regions like Nigeria where more cost-effective and less resource-intensive solutions are desperately needed.

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