CEO Mads Jarner Brevadt tells us about Radiobotics’ aspirations for Data Pitch and beyond.


Describe your Data Pitch challenge idea


Medical imaging is crucial to the diagnosis of many conditions, helping doctors confirm accurate diagnoses and set treatment for their patients. With the ageing population ever-increasing, the amount of images being taken has grown rapidly. Currently, all images need to be described manually, putting more pressure on the healthcare system. Our aim is to help healthcare professionals describe medical images faster and more objectively, by using machine learning algorithms to form decision support tools. Our focus is on images of bones and joints, millions of which are taken every year.


What does the idea set out to achieve?


With successful implementation of our data-driven algorithm, healthcare professionals will be just a click away from having access to objective insights by an automatic analysis of the image. This will minimise risk of misdiagnosis, free up time for more urgent and complex cases, and eventually improve the patient outcome and experience.


What makes your idea different or unique?


The rapid development of new tools within machine learning and computer vision have accelerated the development of automatic analysis of image data within healthcare. While many focus on helping doctors in acute diagnostics such as diagnosing cancers, Radiobotics’ aim is to aid the diagnosis of more routine, non life-threatening cases within radiology. We have domain knowledge, access to validated data and well-respected opinion leaders, all of which can help us shape our product, and ensure that it will have a huge clinical impact, improving our healthcare systems and saving time.


Where did the idea come from?


The idea originally came from working with doctors and listening to their clinical needs when working with medical images. This, combined with our knowledge of the technical possibilities of using machine learning with images, led to us looking into potential possibilities. It was obvious that there was plenty of opportunity to create clinical decision support tools that will, in the future, help the brilliant radiologists in our healthcare systems.


What excites you about the challenge you applied for?


We have an opportunity to make a big difference, helping not only doctors and healthcare systems, but also to benefit patients who could receive more precise, timely diagnoses and treatment. Our choice to work within healthcare was made many years ago, and was inspired by the opportunity to create new tools to promote good health, as well as the opportunity to be truly impactful for real people with real problems. Solving this is an extremely exciting challenge for the Radiobotics team, a challenge we would like to face head-on.


How did your team meet?


Our team met over 10 years ago, on a biomedical engineering course. Throughout the years we have collaborated on many projects together, and we consistently challenged each other and the boundaries of technological possibility in healthtech. We finally found the right challenge, leading to the founding of Radiobotics – a small and dedicated team with big ambitions!


What’s the best thing about working with data?


Working with data, and particularly medical data, brings with it an interesting challenge. The potential for impact of medical data is huge, and still largely untapped. A possibility is to optimise the clinical workflow by providing decision support,  and another is the potential to extract new detailed information from the data which has never been available before, due to the fact that the complexity of the data often overtakes human analytical capability. The data is already there for the most part, so the thought of achieving these goals by putting the data to work is very rewarding.