Aidoc Kicks Off RSNA Showing Why Radiologists Lead the Way in Healthcare AI
Aidoc's AI-driven care solutions focus on connecting all points of care through new functionality and expanded solutions showcased at RSNA
CHICAGO, Nov. 27, 2022 /PRNewswire/ -- Aidoc, the leading provider of healthcare AI solutions, enters the Radiological Society of North America's (RSNA) 2022 annual meeting with a series of recent clearances, accolades and investments demonstrating the continued rapid adoption—and massive potential—of artificial intelligence.
"From new funding rounds to expanding our solutions to cover multiple service lines, Aidoc has experienced numerous milestones since our time at RSNA last year," said Elad Walach, co-founder and CEO, Aidoc. "Yet, we remain steadfastly focused on where we started – with radiology. We believe radiology practices are the AI champions and early adopters within health systems., As the most established healthcare AI users, these physicians can help guide hospital leadership to invest in AI solutions to further improve patient and financial outcomes."
Accolades and Enhancements for aiOS™
What started with image-based AI has quickly expanded to further connect and maximize the care experience through Aidoc's proprietary aiOS™, a first-of-its-kind operating system that enables organizations to reliably deploy AI solutions in high volumes and overcome the challenges associated with legacy IT systems and separate physician workflows. Named "Best New Radiology Software" at the prestigious 2022 AuntMinnie.com awards, Aidoc is further enhancing aiOS' patient management offering by enabling an always on, automated end-to-end platform for patient care and coordination.
Additionally, Aidoc is now available in the Epic App Marketplace, enabling efficient integration with Epic's Electronic Health Records (EHR) platform. By integrating with Epic, Aidoc's aiOS streamlines clinical workflows and automatically provides physicians with real-time clinical information andactionable AI insights on patient care.
Introducing New Patient Management Functionality
An estimated 12 percent of patient cases recommended some type of follow-up1. The challenge is that health systems often lack a closed-loop communication system, encumbering ordering clinicians and teams with the onerous task of manually connecting all the dots through disparate systems that don't communicate effectively. This could potentially add hours of more work to an already overburdened system and risk patients falling through the cracks.
Aidoc's patient management solution removes those system barriers by creating an end-to-end process automating the recommendation of potential follow-up actions with deep integration into the EHR, resulting in closed-loop patient care.
"Our newest offering enables teams to not only manage needs in active cases but also draw attention to potential unexpected findings that may need timely care and management," stated Demetri Giannikopoulos, vice president of innovation, Aidoc. "We make follow-up easy, connecting the dots along the patient's pathway of care."
The impact of Aidoc's technology is also apparent in the 16 abstracts being showcased at RSNA, including a retrospective study presented by Envision Healthcare exploring Effectiveness of a Convolutional Neural Network Artificial Intelligence Algorithm in the Detection of Intracranial Hemorrhage on Noncontrast CT Imaging. In the retrospective study, Envision Healthcare looked at 8,468 CTs from 29 different facilities and demonstrated robust sensitivity/specificity (94%/99%) along with a potential enhanced triage rate of 5.8 percent.
Aidoc will have an on-site booth in McCormick Place during the RSNA Annual Meeting where attendees can demo the end-to-end radiology experience and see firsthand how the exclusive aiOS functions as an always on extension of hospital health systems that enable facilities to build an intelligent and connected health enterprise.
1 Cochon, L. R., Kapoor, N., Carrodeguas, E., Ip, I. K., Lacson, R., Boland, G., & Khorasani, R. (2019). Variation in Follow-up Imaging Recommendations in Radiology Reports: Patient, Modality, and Radiologist Predictors. Radiology, 291(3), 700–707. https://doi.org/10.1148/radiol.2019182826
SOURCE Aidoc Medical LTD
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