How to power your hospital with artificial intelligence in medical imaging

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How to power your hospital with artificial intelligence in medical imaging

Press releases may be edited for formatting or style | April 06, 2021 Artificial Intelligence Health IT Telemedicine
SANTA CLARA, Calif., April 6, 2021 /PRNewswire/ -- The medical imaging industry is in the midst of large-scale transformation, largely driven by the advancements in technologies such as artificial intelligence (AI) and analytics, digitalization of radiology, as well as the rise of precision medicine and teleradiology. These cutting-edge technologies are aimed at addressing challenges in clinical, operational, and staff and patient experiences. In addition, they will resolve critical business pain points such as reimbursement cuts, sub-optimal use of imaging, radiologist burnout, missed appointments, and shortage of radiology subspecialists.

Frost & Sullivan's latest white paper, A practical Guide for the Implementation of Artificial Intelligence in Medical Imaging, highlights the major challenges in imaging and explores how AI can be leveraged to solve these challenges. It also covers the likely pitfalls during the implementation process and some of the key factors to consider for the successful implementation of an AI program. Furthermore, it reveals how this pandemic presents an opportunity for technology companies to prove their claims by demonstrating a positive return on investment (ROI) from clinical, operational, and financial perspectives.

To download the complimentary white paper, please visit:

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"A standards-based and interoperable enterprise imaging platform forms the robust framework needed to integrate AI algorithms within the clinical workflow with ease. Implementation of AI algorithms in siloes will lead to the scattered and isolated realization of intended benefits by the provider organizations," observed Dr. Suresh Kuppuswamy, Healthcare & Life Sciences Industry Principal at Frost & Sullivan. "To have a successful implantation of an AI program, hospitals should focus on aligning with a technology partner who can relieve them of the arduous tasks of exploring, validating and integrating various algorithms for a specific clinical application."

"Another important consideration is the seamless integration of the AI program into the existing radiology workflow. With RUBEE™ for AI, our approach of building an ecosystem of augmented intelligence powered by machine learning and workflow automation engine is unique, logical, and builds the foundation for our client's future growth," noted Dr. Anjum Ahmed, Global Chief Medical Officer at Agfa HealthCare. "By providing diagnosticians with carefully curated AI decision support tools, embedded in their Enterprise Imaging solution, we support them to maximize the value of their own skills and expertise, and become consultative powerhouse of evidence-based intelligence."

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