Building on the successful U.S. launch at the SBI/ACR Breast Imaging Symposium, DetectedX, the leaders in intelligent interactive educational technology, will showcase updates to its Radiology Online Learning Platform at the 108th Annual Radiological Society of North America (RSNA) meeting, November 27-December 1, 2022 . At RSNA, DetectedX will launch ImageDx, a fully customizable, interactive learning platform providing users the ability to design and deliver image-based education using DetectedX's award-winning templates and approaches. Educators can leverage existing DetectedX content or load their own images, quizzes and other learning content for easily accessible and secure online learning. The next generation technology transforms the teaching and learning experience for clinicians, teachers and students alike. For more information or to schedule an appointment, visit DetectedX RSNA 2022. DetectedX announced recently that Professor László Tabár, a Nobel Prize Nominee and visionary physician, academic and educator, has joined the company as Medical Director of Breast Imaging. DetectedX will showcase the new breast imaging educational content from Professor Tabár at RSNA. To view the new education content, visit https://detectedx.com/laszlo-tabar/ With momentum building in the marketplace, DetectedX is adding a number of new users from large radiology groups, national screening centres, academic centers to individual radiologists, across the US, Europe, Middle East and Asia. In addition, the company is developing new partnerships to foster the development and delivery of the highest quality education. For example, Professors Wendie Berg and Margarita Zuley are looking forward to working with DetectedX in a new collaboration with UPMC. This exciting new collaboration will ensure that first class education is delivered to all those with an interest in breast cancer imaging. Innovative interactive technologies will blend with the world's best clinical educators to ensure that on demand education is available to anyone, anywhere 24/7. The company will also showcase new subscriber options for users across a broad range of breast imaging organizations, including Screening environments, Clinics/Radiology Providers, Universities, Private Practice Radiologist Groups and Individual Radiologists. Users can customize access to the intelligent interactive educational platform, which features micro-learning tools, including quizzes and expanded educational content and videos, as well as CME and accreditation dashboards. New learning tools will feature new breast and lung educational content, as well as Medical Physics, Radiation and Artificial Intelligence topics. Designed to improve radiologists' ability to correctly detect breast lesions in 2D and 3D Mammography, the Radiology Online Learning Platform has been proven to help clinicians improve the ability to detect and diagnose breast cancer cases, showing a 34% improvement in the accuracy of diagnosing difficult cases. DetectedX's Radiology Online Learning Platform is currently used in more than 150 countries, including national screening services, clinics and professional societies in North America, UK, Australia, Ireland, New Zealand, Slovenia, Italy and Vietnam. In addition, DetectedX has marketing and distribution partnerships with Volpara Health, Fujifilm and GE Healthcare.
"Since launching into the U.S. at SBI, we have experienced tremendous momentum with new customers, new subscriber options, and exciting new educational content. We are excited to return to the U.S. and showcase the expanded DetectedX team focused on enhance our breast imaging educational content and help us improve radiology education around the world,"
Professor Patrick Brennan, CEO DetectedX and Chair, Diagnostic Imaging, the University of Sydney.
ABOUT DETECTEDX
DetectedX's Radiology Online Learning Centre, focusing on diagnostic accuracy and driven by artificial intelligence, is revolutionizing disease detection in 150 countries. The on-demand, web-based training platform has been proven to improve the accuracy of diagnosing difficult cases by 34%.