When I first told people I wanted to become a radiologist, they all looked at me if I was going to embark on the Titanic. Very often I’m asked if I’m not afraid that the field of medicine I work in will be replaced by artificial intelligence in a few years. The answer is no. In fact, being a radiology resident, I’m highly excited about the potential that the field of radiology has for redefining the future of healthcare. Currently, this medical specialism is one of the first to start implementing and developing AI tools to improve the accuracy and speeds of diagnostics. This is highly necessary because of the enormous and exponentially increasing amount of radiology exams that are being made nowadays. Luckily, a lot of smart teams, universities and companies are busy building tools to reduce the workload of radiologists, to ensure the high-quality standards of diagnostics we all rely on.
There is only one strange thing I noticed. Hundreds of AI solutions have already been developed, but only a few make their way to clinics and above that, the majority has not shown to change care for patients. I started to incentivize what are the obstacles and found that there are many. However, the main obstacle is a lack of alignment between industry and hospital staff. So this was inspiring. What if we could just turn things around and start from scratch?
Together with my former study friend Damiaan Sprenger and a team of highly talented #AI developers we started building a platform for cloud-based AI implementation: #Holland AI.
We have launched our first application (PulmoFast) in the Maasstad Hospital in the city of Rotterdam (i.e. the best city in the world). From day 1 we talked and worked with all the hospital staff involved in the implementation (i.e. doctors, radiographers, IT-staff, physicists, legal officers, security officers, and so on). This approach has been instrumental in rapid deployment, and co-creation.
Also, we had great knowledge of support from #Microsoft. This eventually resulted in an implementation study of our algorithm for the detection of pulmonary nodules (potential precursors of lung cancer), which we call the #PulmoFast algorithm.
We expect to publish results of PulmoFast soon. Tip of the veil: it works pretty well! We are working on a bunch of other exciting projects at this moment, and we can’t wait to share developments with you on LinkedIn.If you’re interested in our activities, feel free to reach out to me on Linkedin!