We are on the verge of another transformative phase in the industry by rationally and appropriately unlocking the expanding potential of technologies like artificial intelligence.
Recently I had the opportunity to discuss this topic with a broad group of health leaders and radiologists. Our conversation reminded me of a story from 1997 when chess grandmaster Garry Kasparov played the computer Deep Blue and lost, which many saw as the moment artificial intelligence proved itself to be superior to human intelligence. But just a few years later, during a “freestyle” chess match, in which teams could be made up of any combination of humans and computers, a duo of amateurs with three simple machines beat the world’s most powerful chess computer at the time, Hydra. By letting the computers use their abilities to plan short-term tactical moves, the humans could work out the big-picture game strategy – this approach showed that people can be empowered to do what they do best when intelligent systems do the heavy lifting.
My sense is that this combination of human and machine is very much applicable to how we can use AI to assist us in Radiology.
Although our North Star may be precision health, we have a very long journey ahead of us. Today we are focused upon the precision diagnosis stage, which uses an intelligent combination of imaging and other disparate types of information to make a more confident diagnosis. Today’s technology and innovations are already making it possible to more quickly and accurately reach these diagnoses. More confident diagnoses mean caregivers have a better understanding of what patients need and the opportunity to put it into action. Then comes precision medicine, which aims to provide the right treatment for the right patient at the right time. This is also being used today, primarily in cancer care but increasingly with other diseases. Precision health is the ultimate goal, which aims to use a higher level of intelligence to preemptively determine patients predisposed to certain diseases and conditions. Precision health will not only help personalize care, but also define early screenings and keep people out of the hospital.
Achieving precision health will require a significant undertaking with the merging of many different technologies and sub-specialties and shifting from a reactive to proactive approach when it comes to caring for patients. Over the next few decades, we must switch to a more proactive mindset and focus on preventative measures that will lay the groundwork for reaching precision health. Today, preventing disease means taking many courses of action, sometimes when it is already too late, like monitoring weight, increasing exercise, and quitting smoking. We are approaching a time when understanding a patient’s genetic predisposition for developing disease later in life can be more broadly adopted.
To achieve this, radiology needs to take action now and become an integral part in a complete diagnosis and treatment ecosystem that seamlessly integrates people, technology and data to deliver a shared and holistic view of each patient. By giving healthcare professionals the tools, analytics and insights needed throughout the patient journey to truly drive toward precision diagnosis, they are able to take a central role in the full clinical care of patients.
AI should be considered an enabling technology that can empower the radiologists in ways unimaginable just a few years ago. With the appropriate use of AI, the radiologist can play a much more active role in the entire patient journey.
Just like the freestyle chess team, technologies like AI allow radiologists and the entire care team to do what they do best. Intelligent solutions make sense of the data and deliver contextual insights across the care continuum, which is the equivalent of the short-term tactics in the chess game, while people focus on specific strategies to more effectively manage the patient’s well-being
I believe achieving precision diagnosis is foundational to delivering upon precision medicine, and as a result, radiology will have a significant role in shaping the future of healthcare. With healthcare providers and machines using different strengths to go beyond delivering one single point of information, we eventually progress to making precision health a reality.