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 Colorado State University are pinpointing potential hotspots for COVID-19 transmission with cellular wireless network data, which could help regions manage risk.
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Researchers from Binghamton University, State University of New York have developed several predictive analytics models to examine COVID-19 trends and patterns around the world.
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A team from Florida Atlantic University’s (FAU) College of Engineering and Computer Science is leveraging machine learning technology to build a COVID-19 knowledge base and risk assessment...
The Food and Drug Administration (FDA) is leveraging real-world data to better understand COVID-19 risk factors, tailor public health interventions to specific communities, and mitigate the spread of...
Parkland Center for Clinical Innovation (PCCI) has developed a big data analytics dashboard to accurately identify communities at high risk for COVID-19 infection.
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As the healthcare industry continues to seek solutions to track and control the spread of COVID-19, patient matching and data standardization have surfaced as effective responses to the pandemic.
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Howard University College of Medicine’s 1867 Health Innovations Project and AARP Innovation Labs will leverage artificial intelligence and data analytics to boost chronic disease management in...
The All of Us precision medicine research program announced that it will evaluate the spread and effects of COVID-19 through antibody testing, a survey about the pandemic’s impact, and EHR...
Cleveland Clinic researchers have developed a predictive analytics model to determine an individual patient’s likelihood of testing positive for COVID-19, as well as their potential outcomes from...
When COVID-19 first started spreading across the country, hospital capacity and the allocation of resources were among the top concerns for healthcare leaders.
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When evaluating COVID-19 data to inform policies, decision-makers should consider five criteria to better understand the spread of the virus in their communities: representativeness, potential...
In the healthcare industry today, it is widely understood that optimal health outcomes require addressing patients’ clinical and non-clinical needs – their social determinants of...
The interaction of COVID-19 and existing chronic diseases – including diabetes, obesity, and hypertension – are associated with poorer outcomes from the virus, indicating that health...
COVID-19 death rates in the US are correlated with patients’ age, race, socioeconomic status, and other social determinants of health data, according to a study led by researchers at the MIT...
Black men who have received heart transplants may be at increased risk for worse outcomes with COVID-19, indicating gender and racial disparities that warrant further research, according to a study...
In the race to find potential treatments and therapies for COVID-19, genomic data is being generated with unprecedented frequency.
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The Mount Sinai Health System has received a grant from Microsoft AI for Health that will support a new data science center representing expertise in care delivery, health sciences, and artificial...
The World Health Organization (WHO) is leveraging data analytics and cloud technologies from Amazon Web Services (AWS) to accelerate global efforts to track, contain, and understand COVID-19.
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The National Quality Minority Forum (NMQF) and Centene Corporation have launched a research partnership to evaluate the health disparities caused by COVID-19 in minority and underserved...
