This is the first in Ellumen’s new series on AI Innovation in Medical Imaging
Artificial Intelligence or AI technology, a broader term that often encapsulates Machine Learning (ML), Deep Learning (DL), Neural Networks (NN) and Robotic Process Automation (RPA), is ubiquitous in our lives today. Whether you are asking Alexa what the weather is like outside, depositing a check on your mobile banking app or taking an Uber home from the office, you are leveraging AI technology. As consumers, we are reaping the benefits of AI daily in the form of a more personalized user experience, more efficient service and ultimately, greater customer satisfaction.
As healthcare systems across the world strive to improve clinical outcomes and increase efficiency, AI stands out as a technology with the potential to revolutionize the healthcare dynamic. The value of collecting, analyzing and ultimately driving clinical decisions based on a robust data set is not a novel concept. In fact, this method is universally recognized as best practice by clinicians and healthcare administrators around the world. As a tool to support clinicians, AI offers the prospect of simultaneously enhancing scale of data input while improving the speed and efficiency of analysis and decision making. This capability is particularly advantageous to clinical disciplines with extremely large and complex data sets like medical imaging.
A recent study from Definitive Healthcare found that over half (53%) of responding organizations (hospitals and medical imaging centers) say that they will be utilizing AI within the next two years to either perform or assist in patient imaging or business operations. The application of AI in medical imaging has already proven its ability to increase productivity, reduce errors, improve diagnostic accuracy, enhance predictive analysis and reduce expenditures: