RadNet to Acquire DeepHealth, Expanding its Efforts in AI – AiThority

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RadNet to Acquire DeepHealth, Inc., Expanding its Efforts in Artificial Intelligence

AIT News Desk 16 Mar 2020 Machine Learning, News Leave a comment 5 Views

RadNet, Inc., a national leader in providing high-quality, cost-effective, fixed-site outpatient diagnostic imaging services reported it has executed a definitive agreement to acquire DeepHealth, Inc. (“DeepHealth”), a leading radiology artificial intelligence (“AI”) and machine learning company initially focused on solutions for the medical interpretation of mammography exams.

Founded in 2015 and based in Cambridge, Massachusetts, DeepHealth is developing solutions in machine learning and AI to assist radiologists and other clinicians in interpreting images and improving patient care. DeepHealth’s development to date has focused on screening mammography, specifically 3D breast imaging, where the large volume of cases and the difficult nature of their interpretation place significant demand on radiologists.

RadNet will purchase DeepHealth for an initial payment of approximately 1.0 million shares of RadNet Common Stock to be made at closing, which is planned for April 1, 2020. Additional payments to DeepHealth equityholders aggregating up to approximately 1.5 million shares will be contingent upon the achievement of several significant milestones, including establishing approval from the Federal Drug Administration (FDA) for certain mammography and prostate MRI algorithms and for demonstrating certain features, functionality and radiologist productivity.

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Upon closing of the transaction, Dr. Gregory Sorensen, Co-Founder and President of DeepHealth, will join RadNet to lead all of RadNet’s AI efforts, including those projects currently being developed by RadNet’s previously acquired Nulogix team. Dr. Sorensen’s responsibilities, in addition to continuing the management of DeepHealth’s staff and initiatives, will include directing RadNet’s AI strategy, acquisitions, partnerships, licensing and product development. A graduate of Caltech, Brigham Young University, Harvard and MIT, Dr. Sorensen is a board-certified neuroradiologist, was a full professor at Harvard Medical School and co-directed a 300-person laboratory inside Massachusetts General Hospital. Immediately prior to founding DeepHealth, Dr. Sorensen was the President & CEO of Siemens Healthcare North America. DeepHealth’s Co-founder and Chief Technology Officer, Bill Lotter, a Harvard University PhD graduate, will help deploy and further develop DeepHealth’s AI technology within RadNet.

Dr. Howard Berger, Chairman and Chief Executive Officer of RadNet, noted, “We are more certain today than ever before that artificial intelligence will transform the diagnostic imaging and radiology industry. Machine learning, big data applications and automation algorithms will allow us to deliver our services more cost effectively, efficiently and accurately. We have been tracking DeepHealth’s progress and evaluating its algorithms for some time. Not only do we believe Greg and his talented team of developers and computer scientists are leading the field in AI solutions for mammography, but DeepHealth’s core competencies and human resources are the perfect combination to direct other important RadNet AI initiatives.”

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Dr. Berger continued, “As a reminder, we spend almost 20% of our globally-billed net revenue on the radiologist interpretation of our images. In 2019, we completed approximately 1.4 million mammography exams, representing approximately 17% of our procedural volume and 15% of our revenue. We believe AI will create workflow efficiencies and improve the accuracy of image interpretation in mammography and in other modalities we perform, which can materially benefit all of RadNet’s stakeholders.”

Dr. Sorensen of DeepHealth, noted, “My team and I are thrilled to join the RadNet family. RadNet is unique in the imaging business and positions us to be successful in our mission to create industry-leading AI products and services that have significant impact on patients’ lives. Our whole team is excited to build on the unparalleled scale and capabilities of RadNet. As a result of RadNet’s operation of 335 facilities in some of the busiest markets in the country and performance of over eight million exams per year, its database of stored images and corresponding radiologist reports is as broad and as deep as any of which we have identified anywhere in the world. Furthermore, RadNet affiliates with over 700 radiologists and owns its own information technology infrastructure in eRAD. It has unparalleled relationships with referring physicians, health plans and capitated payors. I cannot think of a better positioned company to capitalize on AI opportunities and to develop products and services that can transform the entire industry.”

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