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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Abbott’s troponin-I test helps predict CV events in patients without heart disease

Supplementing standard physicals with Abbott’s high-sensitivity troponin-I blood test could boost the accuracy of CVD prediction in middle-aged patients, according to research published in Circulation April 29.

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Participatory health and AI may help each other advance around the world

If AI is to find a foothold across the worldwide healthcare ecosystem, it will need to rest on research into how it may affect the emerging realm of participatory medicine.

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FDA clears AI-powered platform for remote patient monitoring

The FDA has cleared Current Health’s wireless wearable remote patient monitoring (RPM) platform for chronically ill individuals, allowing care teams to track their patients’ health in real-time and act proactively when something looks off.

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ASTRO survey: Prior authorization frustrates radiation oncologists, delays patient care

Prior authorization practices are a significant problem that cause delays in patient care, according to a new survey of more than 650 practicing radiation oncologists.

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USC cardiology fellowship loses national accreditation

The University of Southern California will lose its cardiology fellowship accreditation after more than a year of unrest within the medical school, the Los Angeles Times reported April 25.

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Grocery stores opening AI-powered health clinics

Safeway stores in Arizona are opening health clinics that combine AI, augmented reality and telemedicine to offer grocery shoppers a convenient way to be seen for illnesses and injuries.  

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Machine learning detects autism in disadvantaged children 8,000 miles away

Stanford researchers have demonstrated a way to remotely diagnose autism in children in Bangladesh.

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Machine learning analyzes toddlers’ eye movements to ascertain their age

Using deep learning to tease out factors indicative of age-related variability in the way toddlers gaze at visual stimuli, researchers at the University of Minnesota have shown that the technology can accurately distinguish 18-month-olds from 30-month-olds.