News | Artificial Intelligence | April 15, 2020

behold.ai gets CE Mark Approval for its AI-based chest X-ray diagnosis technology

Chest X-ray diagnosis to rule out normal exams using the Company’s technology could lead to an estimated £100m in cost savings to the NHS per year

#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2

April 15, 2020 — behold.ai has been issued with a CE Mark Class lla certification in the U..K and EU for its AI-based technology that can diagnose chest X-rays as ‘normal’. This is believed to be the world’s first such approval and has the potential to make up to £100m in cost savings for the U.K. NHS, the company estimates.

The algorithm’s high level of accuracy in identifying normal chest X-rays exams means that the red dot platform can be used to speed up the detection of those suspected with Covid-19.

behold.ai and Wellbeing Software recently announced a collaboration to fast-track the diagnosis of COVID-19 in NHS hospitals using artificial intelligence analysis of chest X-rays. A national roll-out would enable a large number of hospitals to triage suspected COVID-19 patients inside and outside of the hospital setting using chest X-rays. This is currently being used as the key diagnostic test for triage of COVID-19 patients. This solution is also useful in dealing with the backlog of radiology cases, such as suspected lung cancer patients.

The CE Mark approval, issued to the company by the British Standards Institute, relates to the full quality assurance system for behold.ai’s AI technology and to the design, development and manufacture of its red dot® platform.

“This is a great result for the company and for our team of quality leaders, AI engineers and clinicians who have worked for years to develop a system that meets the highest quality standards,” said Simon Rasalingham, chairman and CEO of behold.ai. “There is, quite rightly, a big focus on ensuring that the relatively new technology of artificial intelligence produces solutions that have a high degree of accuracy, reliability and scalability. This first in-kind regulatory approval is a key achievement for companies in this sector, the first autonomous AI algorithm to rule out normal chest X-rays.”

“Crucially, at a time when NHS radiologists are increasingly reporting images from home, our technology is fast, safe and effective both inside and outside the hospital setting. For examinations identified by our algorithm as normal, with a high degree of confidence, our results can be automatically accepted as being as accurate as an experienced consultant radiologist, and much faster,” said Thomas Naunton Morgan, M.D., chief medical officer of behold.ai.

The Company estimates that being able to ‘rule out normal’ could save the NHS over £100m per annum through a reduction in outsourcing costs.

Earlier this year, behold.ai received FDA clearance for its red dot® algorithm ‘instant triage’ system in relation to the life-threatening condition of pneumothorax (collapsed lung).

For more information: www.behold.ai.com

Related Content

AIR Recon DL delivers shorter scans and better image quality (Photo: Business Wire)

AIR Recon DL delivers shorter scans and better image quality (Photo: Business Wire).

News | Artificial Intelligence | May 29, 2020
May 29, 2020 — GE Healthcare announced U.S.
Largest case series (n=30) to date yields high frequency (77%) of negative chest CT findings among pediatric patients (10 months-18 years) with COVID-19, while also suggesting common findings in subset of children with positive CT findings

A and B, Unenhanced chest CT scans show minimal GGOs (right lower and left upper lobes) (arrows) and no consolidation. Only two lobes were affected, and CT findings were assigned CT severity score of 2. Image courtesy of American Journal of Roentgenology (AJR)

News | Coronavirus (COVID-19) | May 29, 2020
May 29, 2020 — An investigation published open-access in the ...
The paradox is that COVID-19 has manifested the critical need for exactly what the rules require: advancement of interoperability and digital online access to clinical data and imaging, at scale, for care coordination and infection control.

The paradox is that COVID-19 has manifested the critical need for exactly what the rules require: advancement of interoperability and digital online access to clinical data and imaging, at scale, for care coordination and infection control. Getty Images

Feature | Coronavirus (COVID-19) | May 28, 2020 | By Matthew A. Michela
One year after being proposed, federal rules to advance interoperability in healthcare and create easier access for p
The opportunity to converge the silos of data into a cross-functional analysis can provide immense value during the COVID-19 outbreak and in the future

Getty Images

Feature | Coronavirus (COVID-19) | May 28, 2020 | By Jeff Vachon
In the midst of the coronavirus pandemic normal
AI has the potential to help radiologists improve the efficiency and effectiveness of breast cancer imaging

Getty Images

Feature | Breast Imaging | May 28, 2020 | By January Lopez, M.D.
Headlines around the world the past several months declared that...
In April, the U.S. Food and Drug Administration (FDA) cleared Intelerad’s InteleConnect EV solution for diagnostic image review on a range of mobile devices.
Feature | PACS | May 27, 2020 | By Melinda Taschetta-Millane
Fast, easily accessible patient images are crucial in this day and age, as imaging and medical records take on a new
Off-site imaging companies are playing a key role in the fight against COVID-19
Feature | Coronavirus (COVID-19) | May 26, 2020 | By Sean Zahniser
After the worst of the COVID-19 pandemic has pas
The Philips Lumify point-of-care ultrasound (POCUS) system assessing a patient in the emergency room combined with telehealth to enable real-time collaboration with other physicians.

The Philips Lumify point-of-care ultrasound (POCUS) system assessing a patient in the emergency room combined with telehealth to enable real-time collaboration with other physicians.

News | Coronavirus (COVID-19) | May 26, 2020
May 26, 2020  — Philips Healthcare recently received 510(k) clearance from the U.S.
An example of DiA'a automated ejection fraction AI software on the GE vScan POCUS system at RSNA 2019.

An example of DiA'a automated ejection fraction AI software on the GE vScan POCUS system at RSNA 2019. Photo by Dave Fornell.

News | Ultrasound Imaging | May 26, 2020
May 12, 2020 — DiA Imaging Analysis, a provider of AI based ultrasound analysis solutions, said it received a governm