Double feature made by Balzano on June 29: we presented our vision for AI in healthcare and our digital health approach at FutureMD and Botscamp. Read the summary of our talks at the two events below!
FutureMD: Vision and Future of AI in Radiology
Phyisicians, scientists, and decision-makers from across Austria gathered at the Wissen Transfer Ost (Knowledge Transfer East Center) of the Medical University in Vienna, Austria. On that day, the congress center hosted the event “FutureMD Artificial Intelligence – Chances, Applications, Risks (Chancen, Einsatz, Gefahren)”. Stefan Odermatt was invited to present our view on the future of AI in healthcare.
Austrian radiologists likely to burn out, but AI can help.
In Austria, over 1,700,000 advanced medical imaging exams, between MRI and CT scans, are performed yearly, and this number increases every year. However, the number of radiologists in the country didn’t even reach 1,300 in 2016. This means an enormous image interpretation workload for Austrian radiologists, each one of which should go through nearly 3,000 MRI and CT images every single day. In these conditions, who wouldn’t make a mistake at least once? What’s more, the rate of clinical errors in radiology is as high as it was in 1949, despite the advances in medicine and technology. Luckily, AI and machines with brains can save the day, reducing radiologists’ workload, providing a second pair of eyes 24/7 and a tool for retrospective analysis. Moreover, not only does the system never get tired, it also improves: The more it works, the better its results!
If machines with brains are as good as radiologists, who needs human ones? We do!
Machines with brains will revolutionize the medical field, but they won’t leave medical staff without a job. Eliot Siegel, MD, vice chair of imaging informatics at the University of Maryland School of Medicine, stated emblematically: “I reassure any radiology resident that contacts me to finish their residency. There will be more radiologists – not less – in 20 years.” In fact, a combination of artificial and human intelligence will give the best outcomes: If either the machine or the radiologist is wrong, the other one may be able to spot it. In the end, as Stefan Odermatt pointed out, the final decision rests with the human.
Looking back at medical practice through the ages, it is obvious that physicians no longer do what they used to do a century or even only 10-20 years ago. The same will happen with AI in medicine: Doctors won’t be replaced by bots, but their duties will certainly change.
Botscamp: A Bot for Radiologists
At the same time, hundreds of kilometers away from Vienna, we were presenting how ScanDiags works at the third edition of Botscamp, the first online conference on AI and bots. ScanDiags uses neural networks to detect conditions in knee MRIs, and we aim to expand the solution to 150 conditions in orthopedics. Why the knee and orthopedics, when we see all the major companies focusing on cancer diagnosis and treatment? The answer is simple: Orthopedic disorders are the single largest source of pain and disability globally. According to the World Health Organization, they are responsible for half the chronic conditions affecting people over 50 in the developing world.
In fact, musculoskeletal problems are the major cause of years lived with disability worldwide, and are the most common medical causes of long-term absence from work. In the end, a longer life may not be that pleasant, if the body aches. These facts and more were discussed during our talk! Did you miss it or want to re-watch it? You can find the recording here.