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Annalise.ai Showcases AI Tools for Medical Imaging at RSNA 2022 Annual Meeting and Convention
Saturday, December 3, 2022

Diagnostic-support AI solutions developer to display innovative AI to assist radiology workflow and improve clinical outcomes

SYDNEY and CHICAGO, Nov. 27, 2022 /PRNewswire-PRWeb/ -- Annalise.ai, which was just named 2022's "Best New Radiology Vendor" by AuntMinnie.com, is celebrating yet another stellar year of growth and innovation at the Radiological Society of North America (RSNA) 2022 Annual Meeting.

"Our appearance at RSNA 2022 signals our ambition to transform the power of AI in radiology," said Lakshmi Gudapakkam, CEO of Annalise.ai. "We are creating interpretive support tools that help specialists diagnose and treat patients more efficiently and accurately - and working to set new standards for clinical excellence. I invite you to visit us at Booth #4757 in the RSNA AI Showcase in the South Hall."

Annalise.ai has officially started building up its U.S. team to support growth in North America. The U.S. version of Annalise Enterprise CXR module received a 510(k) clearance from the U.S. Food and Drug Administration (FDA) for use in triage and notification of a subset of chest X-ray findings.

"Our clinical solutions are based on one of the world's largest known radiologist-labeled data sets and are currently available across hundreds of sites in hospitals and dedicated imaging centers worldwide," said Rick Abramson, M.D., MHCDS, FACR, Chief Medical Officer of Annalise.ai. "We are accelerating our efforts to bring next-generation solutions with superior clinical outcomes to support growing radiologist work volumes."

Recently, Annalise.ai was named "Best New Radiology Vendor" by AuntMinnie.com, the authoritative radiology news site. The company was cited for its Enterprise CXR tool and its growing list of advances in the radiology space.

Below is an overview of Annalise.ai solutions and the activities during the upcoming RSNA2022.

Annalise Enterprise CXR, the "Best New Radiology Vendor" of 2022
Annalise Enterprise CXR, launched in 2020, is an AI-powered comprehensive decision-support solution for chest X-rays that detects up to 124 findings. Its AI model is trained on a set of more than 780,000 unique studies with more than 280 million labels sourced from Australia, Europe, and the U.S., and its validation study was published last year in The Lancet Digital Health.

Annalise Enterprise CXR is one of the only decision-support AI solutions for chest X-rays that analyzes up to three images, including lateral images. In addition to the recognition by Aunt Minnie, the solution received accolades from MedTech Breakthrough, an independent market intelligence organization that recognizes the top companies, technologies and products in global health and medical technology.

"The accelerated growth in medical imaging has raised expectations on radiologists to diagnose patients accurately and at speed," said James Johnson, Managing Director, MedTech Breakthrough. "Annalise Enterprise, with its innovative use of AI, helps clinicians by presenting a comprehensive list of findings that are the most clinically necessary and helpful to them in order to better inform patient care."

Annalise Enterprise CTB, one of the world's most comprehensive decision-support solutions for non-contrast CT brain
Last month, Annalise.ai unveiled Annalise Enterprise CTB, with an algorithm that can identify up to 130 suspected findings, including conditions that require time-sensitive interventions. This assistive clinical tool empowers radiologists with a "second set of eyes" to help them improve overall diagnostic accuracy and clinical outcomes.

"Annalise Enterprise CTB represents a leap forward in AI technology for neuroimaging," added Dr. Abramson. "Most other AI products for head CT can only recognize a smaller subset of findings. Annalise Enterprise CTB helps the radiologist with up to 130 imaging findings. The result is more support for the radiologist and better patient care."

The algorithm in Annalise CTB was trained on one of the world's largest label datasets of non-contrast CT brain studies, hand-labeled by 143 radiologists to generate more than 240 million CTB labels.

Partnerships with a growing number of key industry players
Annalise.ai has partnered with Fujifilm Australia for the distribution of its decision support solution for portable and stationary chest X-ray machines, Annalise CXR Edge. Fujifilm Australia will offer two versions of Annalise CXR Edge. Annalise CXR Edge Comprehensive, which can detect up to 95 clinical findings and is suited for inpatient, outpatient and emergency settings, and Annalise CXR Edge Critical Care, which detects up to 35 findings relevant in trauma, emergency, and intensive care settings.

Annalise CXR Edge will be available in selected Fujifilm equipment models globally, subject to regulatory approvals. It has been registered for clinical use in Australia, New Zealand, the U.K., and India, and approved for use as a medical device in the European Union. Additional partnerships are in negotiation and will be announced shortly.

CE Mark Granted to Annalise Enterprise CXR
Earlier this year, Annalise Enterprise CXR received the CE Mark under MDR Class IIb for use in the European Union. The mark is required for products manufactured anywhere that are sold in the EU and affirms its compliance with Regulation (EU) 2017/745.

Learn more about Annalise.ai at our booth and presentation at RSNA AI Theater.
Annalise.ai will be presenting at the RSNA AI Theater, the meeting's hot spot for the latest topics in AI and machine learning, on Monday, November 28 at 3:30 pm CT. Professor Catherine Jones (Clinical Lead, Chest Imaging AI at the University of Sydney, cardiothoracic lead at I-MED, and clinical advisor at Annalise.ai) and Matthew Lungren, MD, Chief Medical Information Officer at Nuance Communications, will talk about Reimagining AI Within the Radiology Workflow.

Throughout the conference, visitors can visit the annalise.ai team at Booth #4757 - South Hall in the AI Showcase. Senior executives will be available for demonstrations of the Annalise Enterprise CXR solution, one-on-one discussions, and more detailed information about our plans for the North American market. Attendees may schedule demos here: https://annalise.ai/visit-us-at-rsna-2022/

About Annalise.ai
With accelerating advances in medical imaging technology, radiologists and other healthcare providers are now expected to diagnose patients quickly and accurately. annalise.ai fuses the highest quality imaging data with the very best in computer science to produce comprehensive AI clinical decision support solutions, empowering clinicians to make accurate, faster decisions. Our patient-first approach is proudly clinician-led and comes from a deep understanding of the challenges faced in medical imaging. Our AI solutions provide clinicians with a second set of eyes, allowing them to detect with confidence and drive better health outcomes for patients.

Annalise.ai is a joint venture between Australian healthcare technology company Harrison.ai and one of the world's largest radiology companies, I-MED Radiology Network, a partnership that extends the capability of imaging analysis AI to deliver comprehensive modality solutions. The company has offices in Australia, the United Kingdom, the Netherlands, and the U.S.

Annalise.ai solutions are intended for healthcare professionals only. Annalise.ai solutions are not intended to provide direct diagnosis. For detailed device information, including indications for use, contraindications, precautions, and warnings, please consult the user guide prior to use. Not all features are available in all regions, check current regulatory status with an Annalise.ai employee.

Media Contacts
Mary Ann Besser: mailto:maryann.besser@annalise.ai [maryann.besser@annalise.ai __title__ null]
Travis Small: mailto:tsmall@sloweymcmanus.com [tsmall@sloweymcmanus.com __title__ null]

Media Contact

Mary Ann Besser, Annalise.ai, 1 715-386-1665, maryann.besser@annalise.ai

Travis Small, Slowey McManus Communications, 617-538-9041, tsmall@sloweymcmanus.com

SOURCE Annalise.ai



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