ANGELS, November 28, 2022 (GLOBE NEWSWIRE) — RadNet, Inc. (NASDAQ: RDNT), a national leader in providing high-quality, cost-effective fixed-site ambulatory diagnostic imaging services, today announced that its pulmonary artificial intelligence subsidiary, Aidence, and Google Healtha division of Alphabet, Inc. (NASDAQ: GOOG), announce a licensing agreement for Google Health’s AI research model for predicting lung nodule malignancy on CT imaging. Aidence will develop, validate and bring this model to market to support the early and accurate diagnosis of lung cancer and the reduction of unnecessary procedures in screening programs.
Screening for lung cancer with low-dose CT has been shown to significantly reduce lung cancer mortality by up to 24% for men and 33% for women, according to the 2020 NELSON trial. are increasingly implemented in Europe, such as the UK’s Targeted Lung Health Checks. In United Stateseligibility criteria have recently been expanded, further reflecting the benefit of lung cancer screening.
A major difficulty in screening for lung cancer is to establish the nature of the pulmonary nodules detected. Most of these nodules are not cancerous. However, the correct identification and diagnosis of these nodules can be time-consuming, expensive, anxiety-provoking for patients and their families, and sometimes invasive, requiring follow-up CTs or surgical procedures.
Dr. Raymond Osarogiagbon, Chief Scientist, Baptist Memorial Health Care Corporation and Director, Multidisciplinary Thoracic Oncology Program, Baptist Cancer Center, Memphis, TN, explained, “One of the most exciting developments in contemporary population health care is the early detection of lung cancer. Unfortunately, the reality that most of these nodules will be benign presents a real challenge that calls for a technological solution. Artificial intelligence is one of these solutions.
Dr Osarogiagbon continued: “The world is eagerly awaiting the rapid development and validation of software that will improve our ability to find the many needles of lung cancer in the giant haystack that are lung nodules detected by CT scans in current clinical practice.
Deep learning, a subset of AI, has been shown to support malignancy risk scoring of lung nodules. In a study published in Nature in 2018, scientists affiliated with Google Health presented a very accurate model for the classification of malignancies, consistently matching the performance of experienced radiologists.
Aidence has also built a deep learning model for this purpose. Aidence’s algorithm successfully predicts lung cancer from a single scan and was awarded in the 2017 Kaggle Challenge. Its robust performance was further confirmed in a clinical study comparing its performance to that of 11 radiologists on 300 cases.
Help and Google Health intend to complete an AI application for lung nodule malignancy prediction. In this collaboration, Google Health will contribute its scientific expertise. Aidence will further develop the model into a solution for clinical practice and bring it to market, in compliance with data privacy requirements and relevant regulatory standards. The development of this AI application is a statement of intent and no regulatory market applications have been made and no sales orders are taken.
Apart from this collaboration with Google HealthAidence has a proven track record in deploying AI in hospitals and clinics across Europe. His app, Veye Lung Nodules, is currently in use at more than 80 routine practice and lung cancer screening sites.
Marc Jan Harte, co-founder and CEO of Aidence, said, “Our mission at Aidence is to give lung cancer patients a chance. This strategic partnership with Google Health allows us to accelerate and expand our efforts to achieve this.
Mr Harde continued, “We are excited to work on a powerful deep learning model for lung nodule malignancy prediction based on the work of the Aidence and Google teams, as well as to ensure that all other requirements that contribute to the successful deployment of AI in clinical practice are in place, such as clinical validation, certification, and integration into the clinical workflow.
Akib Uddin, Product Manager at Google Healthsaid, “At Google Health, we want to be an active catalytic force in demonstrating the real-world health benefits of AI. We know how important lung cancer screening is to saving lives, and we are excited to play a part in making impact at scale by enabling great partners like Aidence to participate in our research.
About RadNet, Inc.
RadNet, Inc.is the nation’s leading provider of fixed-site, stand-alone diagnostic imaging services and related information technology solutions (including artificial intelligence) in United States based on number of locations and annual imaging revenue. RadNet has a network of 349 owned and/or operated ambulatory imaging centers. RadNet markets include Arizona, California, Delaware, Florida, Maryland, New Jersey and New York. In collaboration with affiliated radiologists, including full-time and per diem employees and technologists, RadNet has a total of approximately 9,000 employees. For more information, visit http://www.radnet.com.
About Google Health
A division of Alphabet, Inc., Google Health is our company-wide effort to help billions of people be healthier. We work towards this vision by meeting people in their daily moments and empowering them to stay healthy and by partnering with care teams and the public health community to provide more accurate, accessible and equitable care. . Our teams apply our expertise and technology to improve health outcomes globally – with high-quality insights and tools to help people manage their health and wellbeing, solutions to transform the delivery of care, research to catalyze the use of artificial intelligence for disease screening and diagnosis, and data and insights to the public health community. https://health.google/
Executive Vice President and Chief Financial Officer
Source: RadNet, Inc.
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