NEW YORK, Feb. 8, 2023 /PRNewswire/ -- RadNet, Inc. (NASDAQ:  RDNT), today announced that it has started implementation of its new Enhanced Breast Cancer Detection (EBCD) service (https://myEBCDmammo.com), which works in concert with a patient's annual breast screening regimen. EBCD includes (i) the application of Saige-Dx™, an FDA-cleared artificial intelligence (AI) technology powered by DeepHealth; (ii) an additional AI-driven review ("Accord") applied to certain suspicious exams and findings; (iii) an in-depth personalized lifetime risk assessment for breast cancer; and (iv) a dedicated 1-800 support line for questions about certain aspects of the patient's reports. EBCD presents a significantly improved level of accuracy in breast cancer detection, empowering women to take greater control of their health.

Patients who visit RadNet's New York and New Jersey imaging networks can benefit from this enhanced screening mammography service if they elect to participate in the EBCD program. Those networks include Lenox Hill Radiology, Borg & Ide Imaging, Hudson Valley Radiology Associates, and the New Jersey Imaging Network.

RadNet is a global leader in the development and use of AI for cancer screening, and the use of AI is significantly featured in the Enhanced Breast Cancer Detection service. "AI is dramatically improving our detection capability and overall quality," said Howard Berger, M.D., President and Chief Executive Officer of RadNet. Gregory Sorensen, M.D., founder of DeepHealth and President of RadNet's AI division, added, "Saige-Dx is a sophisticated, AI deep-learning algorithm that has been trained on more data than any one radiologist would see in a lifetime. Saige-Dx's pivotal study showed that radiologists who used Saige-Dx improved their performance, something no other mammography AI tool has demonstrated. Saige-Dx analyzes each mammogram in detail, and if suspicious findings are present, the AI identifies the lesion in the exam for the radiologist and categorizes the level of suspicion." Senayat Agonafer, M.D., a breast imaging specialist at Lenox Hill Radiology, stated: "EBCD has made me more accurate and efficient as a breast imager. This innovative technology has been trained on a wide dataset of more than one million images. That means I can read more consistently and at a higher performance level across a diverse patient population. That is a distinct advantage for screening in greater New York City."

In the past, many breast screening mammography patients have described a desire for more information about the reports and follow-ups they receive after their annual mammogram, including their lifetime risk of developing breast cancer. While a breast density score, currently required in 38 states, is one factor in a patient's lifetime risk for breast cancer, multiple factors can increase risk. The EBCD service offers a much-needed solution that addresses questions about breast cancer risk by providing a personalized report and a specialist to call when patients have questions about their lifetime risk of breast cancer. Depending on the patient's risk level, their referring physician might recommend a customized screening protocol.

The EBCD service was created for women who want more accurate and informative mammograms. EBCD is the first comprehensive solution of its kind and is described in detail at www.myEBCDmammo.com. According to Dr. Berger, "The EBCD service is one of the most exciting and important endeavors the company has pursued for our patients and staff. It serves as another example of how RadNet continues to lead radiology forward."

About RadNet, Inc.

RadNet, Inc., is the leading national provider of freestanding, fixed-site diagnostic imaging services and related information technology solutions (including artificial intelligence) in the United States based on the number of locations and annual imaging revenue. RadNet has a network of 349 owned and/or operated outpatient imaging centers. RadNet's markets include California, Maryland, Delaware, New Jersey, New York, Florida, and Arizona. Together with affiliated radiologists, including full-time and per diem employees and technicians, RadNet has approximately 9,000 employees. For more information, visithttp://www.radnet.com.

About DeepHealth, Inc.

DeepHealth uses machine learning to distill lifetimes of insights from medical experts into software to assist physicians. DeepHealth's mission is to enable the best care by providing products that clinicians and patients can trust through rigorous science and clinical integration. For more information, visit www.deep.health.