ICAD to Participate in the Guggenheim MedTech Disruptors Summit

NASHUA, N.H., Aug. 10, 2020 (GLOBE NEWSWIRE) -- iCAD, Inc. (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 www.icadmed.com and www.xoftinc.com. 

Contacts:
Media inquiries:
Jessica Burns, iCAD  
[phone]
[e-mail]

Investor Relations:
Jeremy Feffer, LifeSci Advisors
[phone]
[e-mail]

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 https://pubs.rsna.org/doi/10.1148/ryai.2019180096