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GE HealthCare, RadNet Team Up to Improve Breast Cancer Screening

The duo plans to build SmartTechnology solutions that harness AI.

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By: Sam Brusco

Associate Editor

GE HealthCare and DeepHealth, a RadNet subsidiary and artificial intelligence (AI)-powered health informatics firm, have begun a strategic collaboration.

The duo plans to build SmartTechnology solutions that harness AI to help increase the efficiency of imaging interpretation and reporting, allow collaboration among care teams, improve clinical image interpretation, and boost operational efficiency and productivity. The new solutions will merge GE HealthCare’s imaging expertise and scale, RadNet’s care delivery experience, and DeepHealth’s AI-powered health informatics portfolio.

The two companies will initially work to combine DeepHealth’s AI-based SmartMammo and GE HealthCare’s Senographe Pristina mammography system to supports breast cancer screening.

GE HealthCare’s Senographe Pristina was designed to ease the anxiety of a screening with an inviting gantry, elegant lighting, and rounded shapes. It also has a soft-curved surface to welcome patients into a space of comfort and support, GE HealthCare said.

SmartMammo is an AI-powered software-as-a-service (SaaS) solutions that integrates existing breast cancer diagnostic workflows. The solution can support high-volume breast cancer screening programs by embedding imaging informatics into advanced mammography system, the company said. SmartMammo will work to prioritize cases based on suspicion level and ensure integration and interoperability with existing healthcare IT infrastructure.

It also features a cloud-native smart enterprise image viewer with PACS functionality that enables fast image loading and real-time data rendering of multimodality images, accessible from any workstation and location. SmartMammo integrates with the radiologist worklist and reporting tools to streamline the workflow. It has a suite of clinical AI detection tools that offers automatic lesion localization and degree of suspicion.

The duo also aim to include Smart Alerts, a DeepHealth workflow to be integrated with Sonographe Pristina. Smart Alerts will use rapid AI processing to alert imaging sites to cases with potentially suspicious lesions in minutes. This sort of solution looks to enable same-day diagnostic exams, follow-up compliance, and lower anxiety for patients with potentially suspicious findings.

The two companies’ agreement will allow GE Healthcare to distribute SmartMammo and other DeepHealth solutions to imaging providers in the U.S. as part of GE HealthCare’s comprehensive portfolio of imaging technologies.

“We are thrilled to collaborate with GE HealthCare to accelerate the adoption of AI-powered technologies in radiology,” said Kees Wesdorp, president and CEO of RadNet’s Digital Health division. “By combining our pioneering cloud-native operating system, DeepHealth OS, and our AI-powered health informatics portfolio with GE HealthCare’s cutting-edge imaging technology, we are poised to revolutionize large-scale diagnostic and screening programs, streamline radiology workflows, and improve patient outcomes. This collaboration aims to empower healthcare providers with the tools they need to deliver more effective and personalized care at scale.”

“GE HealthCare has a legacy of imaging and AI innovation and is committed to our continued pursuit of new technologies that push the boundaries of what is possible to enable precision care. This new collaboration with DeepHealth harnesses our combined strengths to address critical challenges in healthcare today,” added Roland Rott, president and CEO of Imaging for GE HealthCare. “As we look to make more personalized, patient-centered breast care a reality—AI continues to show great promise in breast cancer screening from early detection and risk prediction, to reduced callbacks and more efficient workflows for breast imaging providers. We are excited to bring the power of imaging and AI together to elevate personalized breast care for those facing this difficult diagnosis.”

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