Throughout the COVID-19 pandemic, predictive analytics tools have played an integral part in healthcare organizations’ response to and defense against the virus.
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Using a predictive analytics model, providers can better project COVID-19 outcomes for improved decision-making and resource allocation, according to a study published in Annals of Internal...
Using machine learning techniques, researchers from Rice University were able to predict the quality of bioscaffold materials used to help tissue injuries heal, according to a study published in Tissue...
With the COVID-19 pandemic impacting US communities in different ways, research and provider institutions have increasingly turned to big data analytics tools to track and monitor the virus’s...
When it comes to healthcare, it seems Americans spend more to receive less.
An aging population, expensive pharmaceuticals, and administrative waste result in sky-high medical costs, while health outcomes remain poorer than those in other...
Parkland Center for Clinical Innovation (PCCI) and Parkland Health and Hospital System have developed a risk index that generates a COVID-19 risk score for each patient using machine learning and big...
The National Institutes of Health (NIH) is offering contracts to seven companies and academic organizations to develop COVID-19-related digital technologies using big data.
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While the rapid spread of COVID-19 has exposed many unflattering healthcare truths, the glaring health disparities highlighted by the pandemic are perhaps the most detrimental to patient health.
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A consortium of research scientists has created a common data analytics model and shared framework that will aim to accelerate COVID-19 research by combining information from disparate EHRs...
A predictive analytics model could spot illicit online pharmacies, enhancing drug safety and patient health, a study published in JMIR revealed.
Online pharmacies have grown in popularity in recent...
In healthcare, providers and lawmakers are faced with the task of making the best possible decisions for patients and the industry as a whole. From choosing the best treatments, to determining the most...
Researchers from Cedars-Sinai have developed a machine learning tool that can forecast data points related to the COVID-19 pandemic and predict staffing needs.
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As the industry continues its quest to provide holistic, comprehensive, and cost-effective care to patients, the term population health management has emerged as a crucial task for organizations to...
A deep learning tool could improve genomic sequencing processes, identifying disease-causing mechanisms that might otherwise be missed by traditional screening methods, according to a study published...
While the spread of COVID-19 has presented healthcare with many challenges, the sheer amount of data generated by the pandemic has been one of the biggest tests the industry has faced so far.
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The Department of Energy (DOE), the Department of Health and Human Services (HHS), and the Department of Veterans Affairs have announced a new big data analytics initiative to coordinate and share...
Scientists at City of Hope and the Translational Genomics Research Institute (TGen) are accelerating precision medicine and personalized treatments for kidney cancer using an advanced genome analytics...
In the midst of a situation as uncertain as the COVID-19 pandemic, the healthcare industry has sought to use big data and predictive analytics tools to better understand the virus and its spread.
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A team from St. Jude’s Children’s Research Hospital have created a genome analytics tool to detect alterations that drive tumor formations, which could help advance cancer precision...
The University of Texas MD Anderson Cancer Center and two institutions at the University of Texas at Austin – the Oden Institute for Computational Engineering and Sciences and the Texas Advanced...