Ajit Patil, Co-Founder, DeepTek, Health News, ET HealthWorld

Shahid Akhter, Editor-in-Chief, ETHealthworld, spoke with Ajit Patil, Co-Founder of DeepTek, to learn more about transforming radiology with deep learning that has the power to improve analysis images and reduce turnaround times.

What challenges and opportunities do you see in AI and radiology?

Radiology is an emerging industry. There is huge potential to integrate AI into the radiology workflow and transform the scenario. AI is powerful in image analysis, image processing and radiology. Much of it is about analyzing images, processing images, and identifying pathologies based on what you see in the images. And therefore, I think AI is well integrated into this space and can bring transformation.

The opportunity to integrate advanced image analysis techniques via AI into the radiology workflow has enormous potential. This has emerged over the past 10 years. AI technology has emerged and has made it possible to analyze images very cost-effectively and efficiently. Over 100 global startups have been funded in this space alone. And then radiology is a vast area. There are different types of modalities addressing different organs of the body. There are so many different types of pathologies. And these startups work independently, trying to cover various fields in the field of radiology.

A few years ago, it was thought that AI could really transform radiology and make it autonomous. And there was a lot of worry and fear. Over time, it became clear that the AI ​​would only be an assistive tool. AI will help radiologists improve productivity, improve quality, reduce turnaround times, reduce errors, reduce fatigue, and help radiologists have a better work-life balance. In this sense, now, AI in radiology is evolving, and there are several areas. There is an opportunity in emergency radiology where a patient following a trauma, accident or other incident has entered the emergency room late at night and you want to quickly identify the challenges . In fact, immediate medication could be delivered to save the patient’s life. There is also public health screening, in which you have diseases like tuberculosis, which are prevalent and you have to automatically identify on x-ray imaging whether the person is infected or not. As a result, I think various opportunities are emerging through AI technology to see the kind of transformation that exists in the radiology workflow. This will bring much needed improvements, making radiology more accessible, making radiology more affordable and making radiology more accurate.


What is the impact of deep learning solutions on this industry?

It was in the year 2000 that deep learning solutions began to impact the industry. Deep learning has incredible power to analyze images and identify objects or segment objects in those images. Radiology consists of analyzing images and identifying lesions in these images. And it was a great game. It was Stanford University that introduced the first algorithms for analyzing chest X-rays. And since then, many developments have taken place. We now have deep learning algorithms to analyze not only cross-sectional images such as CT scans, MRIs, ultrasounds, PET scans and others. And over that time, the algorithms have evolved to become more mature and robust. Additionally, regulatory approval mechanisms, which were previously lacking, have started to take shape and we have now seen some of the algorithms gain regulatory approvals as well.

What are the current deployments of DeepTek platforms?
A major deployment of technology is in Singapore. The Government of Singapore, through its National AI for Healthcare Strategy, is looking for an AI platform that brings AI to the radiology workflow in a very responsible way, and we have been assessed with a number of other competing companies in this sector. We won the tender and our platform is now deployed in nearly five public hospitals in Singapore. Our platform will become the de facto platform for AI in a very transparent and very responsible way. And we look forward to this successful use case in many more countries here. Few radiology platforms are clinically and commercially adopted. DeepTek has worked to enable this. We have been fortunate to have strong support not only from customers but also from industries. So companies like Tata Capital Healthcare Fund and many other global companies have come together to support us through strategic equity investments. In addition, some of the world’s leading IT companies of major medical imaging device manufacturers have also supported us in the go-to-market strategy.


What are the market opportunities for DeepTek?

With this strong base of global clients, global partners and a strong team of over 100 people, I believe we are among the top Indian players here. But there is a huge global market opportunity, and our vision is to see how we can really leverage shared technology in global health, help radiology become more accessible, more affordable, more accurate and, in In this sense, bring about a solid improvement in patient care. We hope to be one of the Indian leaders who can play a very important role in this market.

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