Discover how Aidoc’s AI platform offers seamless end-to-end integration into a facility’s existing IT infrastructure enabling implementation of AI at scale.
Discover how Aidoc’s AI platform offers seamless end-to-end integration into a facility’s existing IT infrastructure enabling implementation of AI at scale.
In the last couple of years, AI for radiology has moved from a tool still in development and unready for the big leagues to piquing the interest of clinicians realizing its potential. Now to widespread implementation with proven value across a range of FDA-approved applications. The Radiological Society of North America’s 107th Scientific Assembly and Annual Meeting this year (RSNA 2021) will showcase how these new technologies are redefining what it means to be a radiologist and how to be empowered by the latest technology. But what accounts for the recent explosion of medical AI solutions, vendors, and use cases?
The AI showcase at RSNA 2019 took place a few months before the pandemic reached the United States in January 2020. Already then interest was high, driven by the promise of AI’s potential to revolutionize medical imaging. Then the pandemic struck, bringing immense pressure to overburdened health care providers with insufficient resources for managing patient inflow. Inversely, imaging departments and clinics suffered in the first few months, due to uncertainty and fears about virus transmission. In some cases, AI had the power to assist in the detection of COVID infection. But for the long term, it had the power to alleviate high workloads. It certainly renewed interest in AI’s potential to support the reading process.
Over the last few months, many health systems found themselves thrust into a sudden rush or looming rush of backlogged imaging cases. At the peak of the pandemic in April 2020, the Neiman Health Policy Institute documented a 90 percent drop off in imaging volume in the U.S., during which many patients—some of which had conditions requiring urgent care—neglected their imaging appointments out of fear. It was not until three to four months later that the institute noticed a recovery to pre-pandemic levels. By then, the damage had already been done and the workload backlog had set in. North of the border, the Canadian Association of Radiologists (CAD) reported last month that 70 percent of radiologists surveyed stated they did not have the sufficient resources to eliminate said backlog.
The community of clinicians and medical imaging technicians are now seeing an opportunity, with the effects of pandemic on their practices clear. With new workload demands calling for tackling the backlog and rapidly-progressing developments, radiologists will be coming to RSNA 2021 with new questions about the potential, best way to access, integration of, and use of AI to improve their workflow and care outcomes.
What to expect from RSNA 2021
At RNSA 2021, general pre-pandemic questions around whether AI can be trusted and if it is effective may be set aside in place of focused, practical ones: Which technologies are the best for my radiology department? Which will improve our workflows and efficiency? How can it be integrated into our workflow? What is the return on investment for this or that option?
Hundreds of imaging-based AI models were developed during the COVID-19 pandemic and, at the time of writing, 343 AI medical devices are cleared for use by the FDA, more than half of these in 2020/2021 and the majority in radiology. One way to make sense of them all is to take advantage of the educational opportunities and vendor displays at RNSA 2021:
The AI Showcase, where the latest in medical imaging and new innovations in AI for radiologists is displayed. Start by visiting the Aidoc booth (#4342) to speak with AI implementation experts, AI users, and see Aidoc’s AI operations dashboard to see what AI at scale means. Schedule a private AI consultation and demo to see how AI is integrated right into the radiology workflow, including care coordination solutions that deliver a multidisciplinary approach to stroke and PE care.
300+ educational courses from every subspecialty where you can connect with peers and radiology leaders to hear how radiology teams are setting the course and executing their AI strategies. Use the RNSA 2021 education program to plan your week. There are also hands-on courses, ‘cases of the day’, and image interpretation sessions. You can earn CME in every subspeciality.
Use the RSNA 2021 industry program to plan attendance at corporate symposiums, ‘lunch and learns’, virtual industry presentations, virtual product theater presentations and virtual AI theater presentations.
Not all AI is created equal, so here’s a handy list of questions to keep in mind about how to establish the value of a given AI solution, which Aidoc developed for RNSA 2019. It should help you to use your limited time wisely. These include questions designed to establish the quality of the data used, understand the product better, and how to think about the return on investment.
AI as a standard of care
There’s good reason to bookmark Aidoc’s Booth 4342. Aidoc has swiftly become the AI of choice and a leading provider of artificial intelligence solutions. Aidoc’s solutions analyze medical images directly after the patient is scanned, notifying and activating physicians within the imaging workflow. The impact on metrics such as turnaround time and length of stay is established: Aidoc’s technology is in use in over 600 institutions worldwide and seven solutions have FDA clearance.
Aidoc recently won the UCSF digital health award for the best new health application of AI, and are proud to be the first radiology solution provider to receive this. It’s confirmation that these solutions reflect the best and most up-to-date clinical practice, and improve workflows across hospitals and other healthcare institutions.
This year, Aidoc went into partnership with Radiology Partners, the largest physician-owned and led radiology practice in the United States. Aidoc offers enterprise AI capabilities to numerous hospitals working with Radiology Partners and healthcare centers in their network, solidifying Aidoc as the AI of choice.
Proving the value of AI in medical imaging
AI solutions provide value beyond improving the speed and accuracy of clinical diagnoses – they can contribute to a significant reduction in length of stay. At Yale New-Haven Hospital, Aidoc’s AI-driven technology for flagging patients with intracranial hemorrhage resulted in a reduction of 59 minutes in ED length of stay and 0.75 days in inpatient length of stay. Researchers at the University of Washington evaluated the performance of a convolutional neural network (CNN) model developed by Aidoc, and found “promising results of a scalable and clinically-pragmatic deep learning model tested on a large set of real-world data from high-volume medical centers.”
This year at RSNA 2021, don’t miss a live presentation from Nina Kottler, MD, MS, Associate CMO of Radiology Partners in the AI Showcase on Monday, November 29, 2021 at 3:30pm CT. In this discussion, “Elevating radiology’s influence across the health system with AI,” Dr. Kottler will share her insights on how radiology can be the AI champions in their institution, now that it’s proven itself beyond just hype. Also learn more about the largest clinical deployment of AI, and how AI is optimizing the radiology workflow while providing value across the healthcare system. Add this session to your calendar and RSVP on LinkedIn.
“You might be surprised how interested [your hospital] really is about buying an AI product, then you as the physician can be the champion of that… educate your fellow radiologists, because we really need to be the earlier adopters of AI and be the winners of tomorrow.” Nina Kottler, MD, MS of Radiology Partners
Redefining Radiology at RSNA 2021
Many radiologists who dealt with the challenges posed by the first wave of the pandemic, have come to understand the potential and value in adopting AI into their workflows. But now RSNA 2021: Redefining Radiology provides the opportunity to explore much more – to choose options for fully-integrated solutions, led by radiology and expanding across healthcare workflows.
As Dr. Marcel Maya of Cedars-Sinai puts it, radiologists are “in the best position to move AI forward”, and can look at it as a way of investing in the field.
Get the blueprint for laying the foundations of AI for your medical imaging center and we’ll see you at RSNA 2021!.
