Experience Stories

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  • artificial intelligence AI predictive analytics

    AI is a game-changer for cardiology—it’s time for practices to get on board

    The use of AI technologies in healthcare has evolved at a breathtaking rate in the last few years. Hype and hypotheticals have been replaced with real, practical tools that help physicians focus on providing high-quality care. 

  • Mimics Viewer

    Beyond AI: How 3D Surgical Intelligence Is Expanding Radiology’s Clinical Impact

    3D surface modeling and virtual surgical planning are expanding radiology’s contribution to multidisciplinary teams. Together, AI-driven interpretation and 3D-enabled clinical collaboration represent two distinct, complementary forces shaping the next decade of radiology.

  • Radiologist

    Bayer: Helping Customers Sustain Patient Care Amid Market Disruptions

    As radiology departments across the US continue to navigate the complexities of the current imaging market, including disruptions in supply chains and increased demand for CT contrast media, one constant remains: the need for reliable, quality supply partners to help sustain patient care. 

  • DocMoonlight

    DocMoonlight and ContrastConnect Announce Strategic Collaboration to Deliver the Industry’s Most Comprehensive Contrast Supervision Solution

    DocMoonlight, the nation’s largest provider of onsite contrast supervision, and ContrastConnect, the largest provider of virtual contrast supervision, today announced a strategic collaboration designed to offer imaging organizations the most complete, flexible, and scalable contrast supervision solution in the industry. By aligning their complementary strengths, the partnership is aimed at expanding patient access, enhancing patient safety, and meeting growing imaging demands across diverse regulatory environments.

  • YNHHS Main Campus

    From Deconstructed PACS to Reconstructed Radiology

    Let’s conduct a quick thought experiment. We enter a time machine and set the controls for Connecticut in 2015. As luck would have it, we land in a meeting room of the imaging department at the Yale-New Haven Health system. There we overhear a conversation. Imaging aficionados that we are, we quickly realize two groups are present—IT leaders and ranking radiologists. It’s hard to make out the exact words through the time warp. However, we clearly hear one term repeated several times: “deconstructed PACS.” 

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ML’s Role in Building Confidence and Value in Breast Imaging

Sponsored by Pure Storage

Countless predictions have been made about artificial intelligence and machine learning changing imaging screening and diagnosis at the point of patient care—and clinical studies and experience are now proving it. Radiologists say the impact is real in improving diagnosis of cancers and quality of care, consistency among readers and reducing read times and unnecessary biopsies. One shining example targets the evaluation of breast ultrasound imaging.

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Will ‘Smart’ Solutions Really Transform Cardiology?

Sponsored by Pure Storage

Smart technologies are often touted as the answer to some of cardiology’s greatest challenges in patient care and practice. But where does hyperbole end and reality begin with artificial intelligence, machine learning and deep learning?

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Matching Machine Learning and Medical Imaging: Predictions for 2019

Sponsored by Pure Storage

Developments in vastly scalable IT infrastructure will soon increase the rate at which machine learning systems gain the capacity to transform the field of medical imaging across clinical, operational and business domains. Moreover, if the pace seems to be picking up, that’s because data management on a massive scale has advanced exponentially over just the past several years. 

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NYU’s Daniel Sodickson on AI, Facebook and Why Faster MR Scans Could Improve Healthcare

Sponsored by Pure Storage

A new project is seeking to make MRI scans up to 10 times faster by capturing less data. NYU’s Center for Advanced Imaging Innovation and Research (CAI2R) is working with the Facebook Artificial Intelligence Research group to “train artificial neural networks to recognize the underlying structure of the images to fill in views omitted from the accelerated scan.”

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Data Analytics: Are They Powering Your Decision-making?

Sponsored by Change Healthcare

Medical imaging is in a big battle with big data. There’s too much data in too many locations, and most often they are not well managed. Data are clearly imaging’s most abundant yet most underutilized strategic asset. 

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A Careful RIS Replacement Emerges as a Key Business-Builder

Sponsored by FUJIFILM Healthcare Americas

If you’ve seen one data center, you’ve seen them all. That’s what Charles Rivers believed, at least.

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A Brooklyn EMR Grows Toward Its Full Potential

Sponsored by FUJIFILM Healthcare Americas

Like every American academic healthcare institution, SUNY Downstate Medical Center in Brooklyn, N.Y., is a beehive of activity in three overlapping yet distinct areas of focus—patient care, physician education and medical research. 

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Transforming Radiologist Workflow: A Q&A on Fujifilm’s REiLI Initiative

Sponsored by FUJIFILM Healthcare Americas

Bill Lacy, vice president of medical informatics at FUJIFILM Medical Systems U.S.A., spoke with Radiology Business about AI’s impact on radiologist workflow and what the company has planned for HIMSS19.

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