Artificial Intelligence is Everywhere
I feel a vibration on my wrist that gently wakes me from my sleep. I roll over, touch the device on my wrist, and lay there for about five more minutes. Then I feel another vibration. I check the time on my phone. It’s 5:30 — time to get up.
My morning ritual starts in earnest: I weigh myself on my digital scale, which shows that my weight is the same as the previous day and automatically syncs with my wearable fitness tracker. As I get dressed, I ask Alexa, a voice-controlled speaker and personal assistant, to play Lose Control by Missy Elliott.
I head to my home office and check my email for updates and alerts. In my inbox, I find a few interesting articles about patient experience that Google has automatically curated for me based on my settings. I make note of the articles, tweet them to the masses, and then slide my laptop into my backpack.
As I get into my car, my phone reminds me that I am approximately 90 miles from work. I turn on the GPS, and it sends me information about road construction, lane closures, and an alternate route that will not add more time or distance to my commute.
I outline this typical morning to illustrate a point about our current reality: artificial intelligence (AI) is all around us. At every point throughout the day, I interface with lots of technology, including some forms of AI. And I am not alone.
AI has crept into many aspects our daily lives. Whether we realize it or not, the very fabric of how we live, work, play, communicate, exercise, and even sleep has become interwoven with AI.
The same thing is happening in radiology.
AI tools are being integrated into radiology that will change how radiologists work, communicate, interact, and make treatment recommendations.
With AI, radiologists will no longer have to manage protocols across all of their clinics and departments. Instead, they will develop personalized protocols based on each individual patient's height, weight, body composition, and clinical history.
AI will also help radiologists identify the most clinically significant findings on imaging exams. As a result, radiologists will no longer spend one minute on 14 different findings, but will instead spend 14 minutes on the most clinically significant finding, as identified through AI, and one minute on each of the other 13 findings that are not of significance.
From there, AI tools will generate prepopulated radiology reports, including all pertinent patient information and clinical findings, while also providing data related to genomics, radiomics, proteomics, and other information obtained from imaging for enhanced patient care.
AI will likely be another tool helping radiologists step out of the dark and into the light — and provide medical imaging care at the N of 1.
By Andy DeLaO, known online as Cancer Geek, is a patient advocate, a senior product marketing manager for a Fortune 100 Medical Technology Company and the Chief Listening Officer for GFHC. He is also a member of the Outreach Committee of the ACR Commission on Patient- and Family-Centered Care and a JACR associated editor.