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    Only two-thirds of U.S. healthcare consumers are OK with surgeons using digital facial recognition to avoid medical error by confirming patient identity. And less than half would greenlight the technology for researchers using diversified image data to advance precision medicine.   These are two key findings from a survey-based study published…

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    • Americans wary of #facialecognition technology in #healthcare | #AI #survey https://t.co/IApBls4cCM

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    Noting that surgical sponges account for 70% of instruments and supplies that inadvertently get left behind in patients’ bodies, researchers say they’ve designed AI software that can flag these “retained” items with good to excellent accuracy. The work was conducted at Nagasaki University in Japan…

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    • The results from an @acsJACS & Nagasaki University study about an AI-equipped tool that finds retained surgical sponges was reported in @AIinHealthcare. Read the full article here: https://t.co/oEbcQX0ZVh

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    While big breakthroughs in healthcare AI seem to have slowed in recent weeks, those involving other hot technologies have kept the content coming for publishers of peer-reviewed medical journals. Here are three such innovations that caught our eye in recent weeks. 1. A wearable strain sensor that functions like “electronic skin” to monitor joint motion and breathing cycles. Researchers at the…

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    • Researchers developed a wearable strain sensor that functions like “electronic skin” to monitor joint motion and breathing cycles via @AIinHealthcare https://t.co/9ObPf65Fpm #wearables #medtech #medinnovations #krystalklear #pulmonaryapps https://t.co/ORce4teQDu

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    True or false? Each time a software developer significantly updates an FDA-approved Software as a Medical Device product, the SaMD faces possible re-review by the agency. Answer: True, albeit leaning hard on possible with a caveat: The stringency of the evaluation process depends on the device’s risk classification and the nature of the change. So reminds the Pew organization in a meaty primer…

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    • How and when FDA assesses the clinical competency of healthcare AI | @aiinhealthcare https://t.co/qRizX3ULGc https://t.co/eCvEWpy4VW

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    Researchers have piloted a deep learning algorithm that can recognize visual cues of sickness, also known as “clinical gestalt,” in facial photos. The team trained the model on 126 photos of healthy individuals in the Chicago Face Database and 26 photos that were digitally manipulated to make members of that subset appear acutely ill. They externally validated the algorithm on photos of 22…

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    • The Telltale Face: Deep learning picks out sickened faces with 100% sensitivity #ClinicalGestalt #MedEd https://t.co/vsoFTfahXA

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    The World Economic Forum has released its 2020 list of 100 tech companies from which to expect big things. Seven of the 100 are in healthcare and, of these, three are based in the U.S. The WEF list of “technology pioneers” highlights growth-stage companies from around the world that the organization believes are “poised to make a significant impact on business and society.” Making the cut in…

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    • 3 US start-ups named healthcare technology pioneers of 2020. Sherlock Biosciences, Verge Genomics, and Vim https://t.co/RJieliMy1U #CardioTwitter @CardioOncCOIN

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    AI-aimed blasting of kidney stones from outside the body hit intended targets at a 75% clip in a proof-of-concept study, pulverizing conventional lithotripsy, which missed the mark almost half the time. The demonstration may have influence beyond its small sample, 11 patients, because the procedure—extracorporeal shock wave lithotripsy (ESWL)—has been losing ground to other treatments that are…

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    • AI-Aimed Lithotripsy Treatment For Kidney Stones Hit Intended Targets At 75% Clip https://t.co/yziT1SGoZc