From Lab Trend Visionary to Dark Group CEO: HPI connects with the Founder and Editor of the Dark Report, Robert Michel
From Communication Strength to Just in Time Reopening at MGH A conversation with Dr. James Brink, Chief of Radiology at Massachusetts General Hospital
Solving Lab Challenges through Recruiting Innovation: HPI connects with Lighthouse Lab Services President, Jon Harol
Providing Value-Based Care in a Pandemic through Telehealth and Data Resources: An HPI exclusive with Dr. Darrel Weaver
Blood Banking is more complex today than ever before. Rob Van Tuyle, President of Vitalant's Blood Division, tells us why.
The Future of Imaging: Assessing the early impacts of COVID-19 and the path to innovation through Artificial Intelligence (AI) A conversation with Dr. Geoff Rubin
Pivoting in a Pandemic: How a U.S. 3D printing manufacturer is helping healthcare in its time of need
CHI Nebraska’s Laboratory Director Connie Wilkins, describes How To Manage a Clinical Laboratory During the pandemic
Former Commercial Lab Leader Highlights the Hospital Lab as the Solution to Community Sustainability in a Healthcare Crisis
Three Phases Essential to Crisis Preparedness in Patient Blood Management with Anne Burkey of St. Luke's Health in Boise, ID
Bringing Clinical Skills to Operational Leadership During a Time of Crisis; Dr. Blanton, Chief Medical Officer at Peterson Health
Reviewing Your Patient Financial Journey with Melody W. Mulaik, President of Revenue Cycle Coding Strategies
PELITAS President and CEO Steven Huddleston Wants Patients to Have a Great Experience – Both Clinically and Financially
How COVID-19 inspired TeraRecon to accelerate their imaging solutions to the point of care with Jeff Sorensen
There are two constants when an amazing new product or technology comes to market: consumers can’t get enough and the critics can’t stop speculating. Those constants hold true for Artificial Intelligence (AI) in medical imaging. And admittedly, the skepticism seemed legitimate at first. A computer classifying, segmenting, and detecting disease? A network telling a radiologist what to read and when? Where does the medical professional fit into this new paradigm? Early on critics introduced the idea of AI completely replacing the radiologist—panic and skepticism ensued.
We’ve all used AI in some capacity in our day-to-day routine. In fact, most people probably don’t realize how pervasive AI is. This isn’t the type of AI that will ever be able to prepare, cook, and serve dinner from start to finish. However, these tools can assist with grocery lists, email, news consumption, and reminders—all in an effort to increase our daily efficiency. Not only is it convenient, these systems save time and money.
Medical imaging has experienced similar outcomes.
The typical workday for any radiologist is high stress. Tedious metrics are used to track productivity, clinicians interrupting them every five minutes on cases, sorting studies just so, in an effort to not miss a critical or STAT procedure. This is where AI comes in. Consider an algorithm that increases the priority of a case based on indications. Or another that can point out potential hotspots for review. Algorithms are meant to increase the end-users efficiently compared to traditional reads and workflow.
AI was never meant to replace the radiologist; in fact, the overall goal was the exact opposite.
So where are we headed next? As the algorithms learn thresholds of acceptance and error, they will continue to get better. We’ve witnessed medical imaging acting as early adaptors of this still new and ever-growing technology. In the last several weeks, CMS approved the first reimbursement opportunity for AI—a triage system for patients with suspicion of stroke. There is a high likelihood that we will continue to see more reimbursement opportunities in the coming months and years. While AI is intended to assist the interpreting radiologist, expedited, high-quality reads with improved patient care, and overall outcomes can’t be ignored.
Artificial intelligence has proven itself worthy of the hype—consumers and skeptics alike are continuing their investment into this growing technology. While COVID-19 continues to affect imaging department volume and elective procedures, COVID-focused algorithms is proving to be a catalyst for AI in imaging, solidifying the pathway to where we’re headed.