CHICAGO--(BUSINESS WIRE)--GE Healthcare today launched the Edison Developer Program to accelerate the adoption and impact of intelligent applications and developer services across health systems. The program is based on Edison, GE Healthcare’s secure intelligence platform, and helps healthcare providers gain easier access to market-ready algorithms and applications by directly integrating these technologies into existing workflows.
For developers, the Edison Developer Program offers a rich set of healthcare services to help accelerate their ability to build innovations that improve operational and clinical outcomes – and also gives them access to scale and the ability to deploy applications across GE Healthcare’s massive customer base. This program expands the existing Edison ecosystem of leading researchers, technology providers and academic institutions who develop, manage, secure and distribute advanced applications, services and AI algorithms to drive real healthcare outcomes.
GE Healthcare also unveiled several new, Edison-powered technologies, including smart devices and intelligent applications, across a variety of clinical areas. These new solutions are designed to make data, insights and clinical context more accessible and actionable across the health system, creating new value for providers and patients — from reducing costs and complexity to increasing the speed and accuracy of diagnosis.
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“We introduced Edison just one year ago at RSNA to help health providers take advantage of data in new and significant ways,” said Kieran Murphy, President and CEO, GE Healthcare. “With the introduction of the Edison Developer Program, and a suite of new intelligent applications and smart devices powered by Edison, we are building on that promise as we continue to work with partners to realize our collective goal of advancing the future of health.”
New Edison Developer Program to Accelerate AI Integration, Advance Outcomes
Investment in healthcare startups is exploding1 – but implementing new innovations effectively can be cumbersome and complex, slowing adoption. For instance, deploying a one-off clinical AI application is currently a manual and disjointed process. Clinicians are looking for a single solution that can span multiple modalities and seamlessly integrate applications or AI algorithms directly into their existing workflows to harness the power of these technologies.2
