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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NIH, NVIDIA to develop AI tools for brain, liver cancer clinical trials

The National Institutes of Health (NIH) and tech company NVIDIA are partnering to create AI tools for clinical trials focused on brain and liver cancer.

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Smartphones could be used to help diagnose depression, study suggests

That smartphone you’re carrying around in your hand could potentially be used as a tool to help recognize signs of depression in patients and lead to earlier intervention, researchers with Stanford University suggested.

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Telemedicine use still rare among physicians

Telemedicine is a growing service, but its use is still rare among physicians, according to a recent research paper published in Health Affairs.

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Aetna, Ascension join blockchain project

Two more healthcare companies have joined a blockchain alliance project that aims to use the technology to improve data quality and reduce administrative costs associated with healthcare provider demographic data changes.

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AI researchers asked to contribute to new platform designed to boost drug discovery

Insilico Medicine, a Maryland-based AI company, is asking researchers to contribute to its new platform aimed at boosting AI-powered drug discovery.

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Stanford researchers use AI to diagnose autism from home videos

A Stanford University research team used machine learning to quickly and accurately diagnose autism in children through short home videos, according to a research article published in PLOS Medicine.

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UMass Memorial partners with AI platform to help monitor patients

The UMass Memorial Medical Center in Worcester, Massachusetts, is partnering with Israel-based company CLEW Medical to integrate an AI analytics platform into its Tele-ICU program to help monitor patients and make predictions about life-threatening conditions.

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Deep learning improves identification of adverse drug events from EHRs

Using a deep-learning model, a University of Massachusetts Lowell research team was able to significantly improve the extraction of adverse drug events (ADEs) from electronic health records (EHRs).