iCAD to Participate in the Guggenheim MedTech Disruptors Summit
NASHUA, N.H., Aug. 10, 2020 (GLOBE NEWSWIRE) -- . (NASDAQ: ICAD), a global medical technology leader providing innovative cancer detection and therapy solutions, today announced that Michael Klein, Chairman and Chief Executive Officer, will present a corporate overview at the Guggenheim MedTech Disruptors Summit, taking place virtually on August 10-11, 2020.
Presentation Details
Date: August 11, 2020
Time: 3:00pm Eastern Time
About iCAD, Inc.
Headquartered in Nashua, NH, iCAD is a global medical technology leader providing innovative cancer detection and therapy solutions.
ProFound AI™ is a high-performing workflow solution for 2D and 3D mammography, or digital breast tomosynthesis (DBT), featuring the latest in deep-learning artificial intelligence. In 2018, ProFound AI for Digital Breast Tomosynthesis (DBT) became the first artificial intelligence (AI) software for DBT to be FDA-cleared; it was also CE marked and Health Canada licensed that same year. It offers clinically proven time-savings benefits to radiologists, including a reduction of reading time by 52.7 percent, thereby halving the amount of time it takes radiologists to read 3D mammography datasets. Additionally, ProFound AI for DBT improved radiologist sensitivity by 8 percent and reduced unnecessary patient recall rates by 7.2 percent.i
The Xoft System is FDA-cleared, CE marked and licensed in a growing number of countries for the treatment of cancer anywhere in the body. It uses a proprietary miniaturized x-ray source to deliver a precise, concentrated dose of radiation directly to the tumor site, while minimizing risk of damage to healthy tissue in nearby areas of the body.
For more information, visit and .
Contacts:
Media inquiries:
Jessica Burns, iCAD
Investor Relations:
Jeremy Feffer, LifeSci Advisors
i Conant, E. et al. (2019). Improving Accuracy and Efficiency with Concurrent Use of Artificial Intelligence for Digital Breast Tomosynthesis. Radiology: Artificial Intelligence. 1 (4). Accessed via /doi/10.1148/ryai.2019180096
