Shahid Akhtar, Editor, ETHealthworld, spoke to Ajit Patil, Co-Founder, DeepTechTo know about the change in Radiology Through deep learning that has the power to enhance image analysis and reduce turnaround time.
What challenges and opportunities do you see in AI and radiology?
Radiology is an emerging industry. Bringing AI into radiology workflows has huge potential to transform the landscape. AI is powerful in image analytics, image processing and radiology. It is mostly about analyzing images, processing images and identifying pathology based on what you see in the images. And so, I think AI fits well in this space and can bring change.
The opportunity to bring advanced image analytic techniques through AI into the radiology workflow holds huge potential. This has come out in the last 10 years. AI technology came forward and made it possible to analyze images in a very cost-effective and efficient manner. More than 100 global startups have been funded in this space alone. And then radiology is a huge space. There are different types of methods for different organs of the body. There are many different types of pathology. And these startups are working independently, trying to cover different areas in the radiology space.
A few years ago, it was believed that AI could actually transform radiology and make it autonomous. And there was much worry and fear. With the passage of time, many clarifications have emerged that AI will only be an assistive tool. AI will help radiologists improve productivity, improve quality, reduce turnaround time, reduce errors, reduce fatigue, and allow radiologists to have a better work-life balance. In that sense, now, radiology AI is evolving, and there are many areas. There is an opportunity in emergency radiology where a patient has come to the emergency room late at night through trauma, accident or some other incident and you want to quickly identify the challenges. In fact, the medicine can be delivered immediately to save the patient’s life. There are also public health screenings, in which you have diseases like tuberculosis, which are widespread and you need to automatically identify on test x-ray imaging whether the person is infected or not. As a result, I believe that various opportunities are emerging to see the kind of change that exists in radiology workflows as a result of AI technology. This will make radiology more accessible, radiology more affordable, and radiology more accurate, bringing much needed improvements.
What is the effect of Deep Learning Solutions On this industry?
It was in the year 2000 that deep learning solutions started to impact the industry. Deep learning has tremendous power to analyze images and identify objects or segment objects in those images. Radiology is all about analyzing images and identifying lesions in those images. And it was a great match. It was Stanford University that came up with the initial algorithms for analyzing chest X-rays. And since then, a lot has evolved. Now we have deep learning algorithms to analyze only cross-sectional images like CT scan, MRI, ultrasound, PET and others. And over that period, algorithms have evolved to become more mature and more robust. Also, regulatory approval mechanisms, which were missing earlier, have started to take shape and we now see some algorithms getting regulatory approvals as well.
What is the current deployment of the DeepTech platform?
Singapore has an important deployment of technology. The Government of Singapore hereby National Healthcare AI strategy, looking for an AI platform that would bring AI into the radiology workflow in a very responsible way, and we were evaluated with some other competing legacy companies in the industry. We won the bid and today our platform is being deployed in about five public hospitals in Singapore. Our platform will become the de facto platform for AI in a very responsible, very seamless way. And we look forward to this successful use case in many other countries from here. Many radiology platforms lack clinical and commercial adoption. DeepTech is working to enable this. We are fortunate to have received strong support not only from consumers but also from the industry. So companies like Tata Capital Healthcare Fund and some other global companies have come together to support us through strategic equity investment. Apart from this, some of the major medical imaging device manufacturers, some of the major global IT companies are also supporting us for market strategy.
What are the market opportunities for DeepTech?
With this strong foundation of global customers, global partners and now a strong team of over 100 people, I believe we are among the leading Indian players here. But the global market has huge opportunities, and our vision is to see how we can really take shared technology into global health, help radiology become more accessible, more affordable, more accurate and, in that sense, bring concrete improvement. Patient care. We hope to be one of the leaders in India who can play a very important role in this market.
