The Future of AI in Diagnostic Imaging and Radiology
Artificial intelligence, more commonly referred to as AI, seems to be the hottest term today, appearing to be useful in every industry from real estate to retail to auto. Healthcare is no exception.
The term “Artificial Intelligence” itself is a broad one. In general, it refers to the field of computer science concerned with creating programs that essentially mimic human intelligence. The most commonly heard AI-related terms for us outside of the computer science world are machine learning, big data, and natural language processing (NLP). Machine learning, at a basic level, refers to systems that can teach themselves. Big data on its own is simply a name for the enormous amounts of data that are available today, and now it is commonly seen as a joint entity with AI, which can process these sets rapidly. NLP teaches computers how to process human language. These just scratch the surface of this burgeoning field but frequently appear in recent diagnostic imaging and radiology research.
Even just in the past year, there have been several developments in the applications of AI technology for the healthcare field. A recent study at Stanford University, for example, suggests that AI could help radiologists to improve their interpretations of mammograms by helping to reduce the number of false positives that can occur due to human error. Diagnostic imaging and radiology oncology are seeing incredible potential from AI to improve accuracy and expedite previously lengthy processes. Illustrating other applications of AI in healthcare in general, an article in Radiology Business by Michael Walter posits that AI can even help physicians with outcome prediction and radiation treatment planning as well as eliminating time spent on clerical tasks.
While these may seem like speculation and that there’s likely a long way to go before this directly affects the everyday patient, recent FDA clearances for technologies like Zebra Med’s HealthICH brain bleed alert and Canon Medical’s Advanced Intelligent Clear-IQ Engine image reconstruction technology make the future of an AI-integrated healthcare system a close reality.
As in other fields, fears of job elimination due to automation have cast a shroud of doubt over the benefits of introducing AI to the radiology and diagnostic imaging disciplines. What does AI mean for clinicians like radiologists? Will the profession become obsolete? Well, according to an article published in Harvard Business Review, radiologists have nothing to worry about. They state that AI is a tool that will allow radiologists to do their jobs better, not do away with them all together.
The future looks bright and exciting as AI technology steps in to help institutions save more lives. To read more about these studies, releases, articles and more at the below links: