Patient Care

This page includes news coverage of various aspects of patient healthcare, including new technology innovations, what is working, what is not, personalized medicine and remote and telemedicine delivery. Find specific news in the areas of Care DeliveryDigital TransformationPrecision MedicineRemote Monitoring and Telehealth.

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Cardiology’s Challenge for the 2020s: Turning the Trend on Rising Mortality

The latest numbers on cardiovascular deaths put the focus on innovative ways to point the trend line down again.

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'Tons of information but not nearly enough wisdom': The state of cardiology in 2019

The past year has seen a whole lot of change for the field of cardiology, but it’s hard to discern where that leaves us as we prepare for 2020. MedAxiom President Jerry Blackwell, MD, MBA, helped clarify the situation.

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CMS selects 25 participants in AI challenge

CMS has chosen 25 participants to advance to Stage 1 of its AI Health Outcomes Challenge, an initiative aimed at developing AI-driven healthcare predictions for providers and clinicians.

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Google will pay $2.1B to acquire Fitbit

Google is taking over wearables company Fitbit for an acquisition price of $2.1 billion, the companies confirmed Nov. 1.

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25 participants advance in $1M AI challenge

CMS announced Thursday, Oct. 31, that 25 participants have advanced in the agency’s Artificial Intelligence Health Outcomes Challenge, putting them one step closer to earning $1 million in prize money.

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Majority of physicians optimistic about AI’s impact on healthcare

Fifty-three percent of physicians say they are optimistic about AI’s potential effect on healthcare, according to a new survey of more than 1,700 physicians published by the Doctors Company.

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AI provides personalized care for MSK disease

Deep learning can provide accurate measurements of a patient’s musculoskeletal (MSK) system by evaluating CT scans, according to findings published in IEEE Transactions on Medical Imaging.

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AI IDs cancer patients at risk of short-term mortality

Machine learning algorithms can be used to identify cancer patients at risk of short-term mortality, according to a new study published in JAMA Network Open. This helps providers plan for necessary conversations about end-of-life preferences.