From past two-three years, there has been a lot of buzz spinning around the implementation of Artificial Intelligence in radiology and how it will be incorporated into medical imaging. As products now obtaining U.S. FDA market clearance (Food and Drug Administration), the questions raised here with this potential technology revolution is how to assimilate the scores of new software applications from a large number of vendors into daily practice.
Most of the new AI software is coming from small startups and each part of software approved by the FDA including very specific medical imaging diagnostic review. Today, experts in radiology have begun asking how AI tech will be feasible into the healthcare centers if it requires hundreds of contracts and incorporation of various incongruent software programs or enterprise imaging system PACS. Nearly 150 companies, at the 2018 RSNA meeting (Radiological Society of North America), demonstrated technology that integrates some level of AI or Deep Learning, and several were focused on Machine Learning. Albeit, just a small number of these vendors actually have an FDA cleared project, but this is expected to rapidly change and many new AI applications for medical imaging will be blow up in the next couple of years. As these emerging technologies may provide advanced outcomes by instantly distinguishing between a hemorrhagic and ischemic stroke, or detect a Pneumothorax during a bedside X-ray, there is uncertainty in the marketplace with regard to how this technology from a large number of vendors can logically be deployed.
Further, there are 4 main areas where AI is being implemented in Medical Imaging, including Computer-aided diagnosis, Clinical decision support, Computer-aided detection, and Quantitative analysis tools. Computer-aided detection has been around for years, but with the addition of Machine Learning algorithms, healthcare experts are calling the newer generation AI-supported software CAD that works, because of its much lower rate of false positives. AI-enabled quantitative analysis tools also are being utilized in Data Analytics software practiced for departmental and hospital business management.