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    Kelli Payne-Gibson

    Artificial Artificial Intelligence (AI) and Imaging: Where We’re Headed

    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.

    Kelli Payne-Gibson

    Kelli Payne-Gibson

    Director, Account Management