How Artificial Intelligence Can Help In Image Transmission of I

  • Artificial intelligence may be important not only to get image sharing technologies to work together – but to make sense of the clinical data.

    Huge volumes of genomic and proteomic data, as well as clinical images – both past and present images – comprise a huge quantity of clinical data. Artificial intelligence is needed for people to use this mountain of clinical data effectively, said Morris Panner, CEO of Ambra Health, an advocate and provider of electronic solutions for sharing patient information.

    “AI doesn’t have judgment. But it does have the ability to categorize and curate data,” Panner said. “One benefit of having more and more compute power is being able to look at clinical problems – to use AI to eliminate some of the variability and roadblocks that stand in the way of recognizing commonalities.”

    Smart algorithms might see patterns in these data, suggesting insights or making correlations, he said. A requisite for doing this is effective electronic transmission of data. “If you can’t move data easily, then you can’t do any of that,” Panner said.

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    Radiology Partners (RP) — the largest physician-owned radiology practice in the U.S. with 1400 radiologists supporting more than 1000 hospitals across 21 states, according to HIT Consultant, provides evidence-based follow-up recommendations — appropriate for patients — to radiologists while they work.

    Radiologist Nina Kottler, vice president of clinical operations at Radiology Partners, helped create and build this machine learning tool into the radiologist workflow. RecoMD alerts RP radiologists to evidence-based best practices and billing conditions before they sign their reports. The idea is to provide information through clinical guidance to the radiologist as they are dictating, she said.