World’s First Online Image-Based COVID-19 Diagnosis Improvement Tool Launched
By MedImaging International staff writers Posted on 03 Apr 2020 |
Image: DetectED-X platform (Photo courtesy of DetectED-X)
DetectED-X (Sydney, Australia), a University of Sydney spinoff comprising radiation and imaging experts, has launched the world’s only online image-based COVID-19 diagnosis improvement tool for healthcare workers. The start-up has directed its breast cancer diagnosis tool at the coronavirus, drawing on pandemic cases globally with support from healthcare and industry leaders to ramp up COVID-19 detection. DetectED-X’s CovED platform, which can be accessed anywhere with an internet connection, is being provided for free and is supported by healthcare experts and leading corporations globally.
DetectED-X’s CovED follows on from the highly successful BreastScreen Reader Assessment Strategy (BREAST) platform, created in 2010 at the University of Sydney, which has been used internationally including in the US and Europe. The cloud-based life-saving technology can help doctors and radiologists diagnose cases faster and more accurately. Computed tomography (CT) lung scans, which produce cross-sectional images using X-rays and computers, are typically used after swabs are taken, to identify the extent and location of the disease; the CT scans produce images within minutes and are also able to diagnose COVID-19 in the very early stages that escape detection with nucleic acid tests.
DetectED-X’s approach, which includes algorithms to improve radiologist skills and identifying where errors were made on images in the online training sessions, has been shown to improve results significantly. Through CovED, individual clinicians can assess their performance on images on screen, and receive immediate feedback, including performance scores used in the industry. The image files personalized for each clinician are instantly returned showing any errors in their virtual diagnosis and the difficulty level is increased over time. As COVID-19 testing ramps up, the platform could facilitate rapid training where required – with modules able to be completed in as little as an hour – upskilling staff unfamiliar with lung radiology to prepare standardized reports for expert review.
“Our platform does not replace expert medical and radiologic training but CovED provides an effective way to recognize rapidly the appearances of COVID-19, which could be critical in a situation of too many patients and not enough expert radiologists, with the modules taking just 1-2 hours to complete,” said CEO Professor Patrick Brennan, medical radiation scientist and educator from the University of Sydney School of Health Sciences, Faculty of Medicine and Health. “This will be immediately crucial in developing countries, where numbers of radiologists are often insufficient – our tests will help people not only diagnose COVID-19 but also identify potentially life-threatening cases wherever they are.”
Related Links:
DetectED-X
DetectED-X’s CovED follows on from the highly successful BreastScreen Reader Assessment Strategy (BREAST) platform, created in 2010 at the University of Sydney, which has been used internationally including in the US and Europe. The cloud-based life-saving technology can help doctors and radiologists diagnose cases faster and more accurately. Computed tomography (CT) lung scans, which produce cross-sectional images using X-rays and computers, are typically used after swabs are taken, to identify the extent and location of the disease; the CT scans produce images within minutes and are also able to diagnose COVID-19 in the very early stages that escape detection with nucleic acid tests.
DetectED-X’s approach, which includes algorithms to improve radiologist skills and identifying where errors were made on images in the online training sessions, has been shown to improve results significantly. Through CovED, individual clinicians can assess their performance on images on screen, and receive immediate feedback, including performance scores used in the industry. The image files personalized for each clinician are instantly returned showing any errors in their virtual diagnosis and the difficulty level is increased over time. As COVID-19 testing ramps up, the platform could facilitate rapid training where required – with modules able to be completed in as little as an hour – upskilling staff unfamiliar with lung radiology to prepare standardized reports for expert review.
“Our platform does not replace expert medical and radiologic training but CovED provides an effective way to recognize rapidly the appearances of COVID-19, which could be critical in a situation of too many patients and not enough expert radiologists, with the modules taking just 1-2 hours to complete,” said CEO Professor Patrick Brennan, medical radiation scientist and educator from the University of Sydney School of Health Sciences, Faculty of Medicine and Health. “This will be immediately crucial in developing countries, where numbers of radiologists are often insufficient – our tests will help people not only diagnose COVID-19 but also identify potentially life-threatening cases wherever they are.”
Related Links:
DetectED-X
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