AI-powered radiology informatics and imaging AI for cancer screening
DeepHealth, RadNet's digital health arm, sells a cloud-native radiology operating system plus disease-specific imaging AI. Its stack spans PACS, HL7, SQL Server and PyTorch across AWS, Azure and GCP, a multi-cloud, multi-framework footprint typical of merged acquisitions, while pain points around legacy on-prem installs and cloud cost show consolidation still underway. Senior-weighted hiring is accelerating across engineering, product and support.
Notable leadership hires: Data Governance Director
DeepHealth is a wholly-owned subsidiary of RadNet and the umbrella brand for its Digital Health segment, headquartered in Cambridge, MA. It combines radiology information and image management systems, PACS and clinical AI for lung, breast, prostate and brain health under one portfolio. Its core platform, DeepHealth OS, is a cloud-native system that unifies clinical and operational data for radiology teams. Customers are imaging centers and radiology departments worldwide, including large cancer screening programs. The company employs 201–500 people and hires in the United States, Netherlands, France, India and Australia.
DeepHealth uses Python, PyTorch, .NET, Java, React, Angular and Node.js, with PACS and HL7 for imaging integration, running on AWS, Azure and GCP with Docker and Kubernetes. It is adopting Ansible.
DeepHealth hires in the United States, Netherlands, France, India and Australia, with recruiting concentrated in engineering, product and support roles.
Current work includes deploying AI medical imaging software, updating its DeepHealth PACS, integrating cloud services with its platforms, and scaling thyroid and breast ultrasound AI products.
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DeepHealth's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.