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Decision Support

By Bill Siwicki | 01:07 pm | February 05, 2020
They will be in the Nuance AI Marketplace for Diagnostic Imaging, which is designed to provide a one-stop shop for radiologists to review and purchase AI models to improve their workflow.
Emerging Technology
By Bill Siwicki | 01:12 pm | January 31, 2020
The medical doctor who heads the consulting giant’s global health practice foresees AI having a huge impact in healthcare this year, and is keeping his eyes on blockchain, extended reality and quantum computing.
By Mike Miliard | 03:26 pm | January 30, 2020
The five-year project will focus on enabling faster medical research innovations, protecting against global health crises and improving access to care, the company says.
By Mike Miliard | 01:12 pm | January 24, 2020
Epic this week sent out an update to its healthcare customers, meant to help providers nationwide detect potential cases of the Wuhan novel coronavirus, or 2019-nCoV.
By Mike Miliard | 03:07 pm | January 23, 2020
As regulatory oversight for predictive decision support evolves, certain best practices can help health systems get the most from machine learning-powered CDS models.
By Bill Siwicki | 12:57 pm | January 17, 2020
The major player in imaging and health IT discusses the trends and some of its technologies with an eye on helping HIMSS20 attendees navigate the show.
By Mike Miliard | 02:53 pm | January 15, 2020
Its new analytics project will apply AI to deidentified data from across Mayo and other health systems, and comb scientific literature to gain insights into new medical advances.
Emerging Technology
By Bill Siwicki | 03:16 pm | January 13, 2020
Five health IT experts from patient experience and patient engagement IT vendor GetWellNetwork open up about what they are seeing as important trends this year.
By Mike Miliard | 03:33 pm | January 10, 2020
FHIR-based clinical data retrieval and an API to more easily share data will help payers, pharma and providers with forthcoming 21st Century Cures rules, the company says.
Cloud Computing
By Nathan Eddy | 11:10 am | January 07, 2020
A study published in Nature suggests its model was able to spot cancer in de-identified screening mammograms with fewer false positives and false negatives than experts.