People’s social behavior, reflected in their mobility data, is providing scientists with a way to forecast the spread of COVID-19 nationwide at the county level. Researchers have developed the first data-driven deep learning model with the potential to predict an outbreak in COVID-19 cases two weeks in advance. Feeding the mobility data to epidemiological forecasting models helps to estimate COVID-19 growth as well as evaluating the effects of government policies such as mandating masks on the spread of COVID-19.
To better coordinate health data projects across the health system and cement its status as a leader in informatics, Penn Medicine is launching a new hub center
According to Chula researchers the volume of online gambling has soared during the COVID-19 pandemic, posing a serious threat to minors, and the government should urgently tackle this problem.
George Slota, a computer scientist at Rensselaer Polytechnic Institute, has been granted a prestigious National Science Foundation Faculty Early Career Development (CAREER) award to develop approaches to matching exascale computers with petascale datasets.
Researchers found that difficulties in diagnosing toddlers with autism spectrum disorder (ASD) might be due to the dynamic nature of the disorder during child development. Children with clinical characteristics that put them on the diagnostic border of autism have an increased susceptibility to gaining or losing that diagnosis at later ages.
UC San Diego was awarded five COVID-19 Rapid Acceleration of Diagnostics (RADx) projects by the National Institutes of Health totaling nearly $33 million, which will fund efforts that range from managing a large data center to expanding testing in disadvantaged communities.
Irvine, Calif., Feb. 9, 2021 — Monoclonal antibodies are showing promise for improving outcomes for COVID-19 patients, but when a hospital is already beyond capacity, administering them can be a challenge. As hospitalizations soared across California, clinicians with UCI Health created a system for delivering monoclonal antibodies that is keeping hospital beds available for patients with the greatest need.
The Data Science for the Public Good program, an Iowa State University project to help Iowa towns harness their data, has led to four offshoot projects to help support community recovery related to economic vulnerability, substance use and general support.
Irvine, Calif., Dec. 17, 2020 —University of California, Irvine health sciences researchers have created a machine-learning model to predict the probability that a COVID-19 patient will need a ventilator or ICU care. The tool is free and available online for any healthcare organization to use. “The goal is to give an earlier alert to clinicians to identify patients who may be vulnerable at the onset,” said Daniel S.
Researchers at the Johns Hopkins Bloomberg School of Public Health have developed a series of case studies for urgent public health issues to help students and practitioners across the U.S. learn how to apply big-data analysis approaches in their work.
In newly published research, scientists have for the first time modeled the nature of solar switchbacks – the large and long-duration isolated velocity spikes in the solar wind that surprised researchers when data arrived from the Solar Wind Electrons Alphas and Protons (SWEAP) instruments aboard NASA’s Parker Solar Probe (PSP).
In a commentary published in the journal Nature Human Behavior, researchers discuss how Twitter’s decision to remove users’ ability to tag precise locations of Tweets might affect research in disaster response, public health and other areas.
Globus, a leading research data management service, reached a huge milestone by breaking the exabyte barrier. While it took over 2,000 days for the service to transfer the first 200 petabytes (PB) of data, the last 200PB were moved in just 247 days. This rapidly accelerating growth is reflected by the more than 150,000 registered users who have now transferred over 120 billion files using Globus.
Fermilab scientists have implemented a cloud-based machine learning framework to handle data from the CMS experiment at the Large Hadron Collider. Now they can begin to use graph neural networks to boost their pattern recognition abilities in the search for new particles.
Iowa State’s rural smart shrinkage project has received a three-year, $1.5 million grant from the National Science Foundation to build upon its pilot study examining whether there were towns in Iowa that have lost population but perception of quality of life has remained stable or improved.
Data shows that coronavirus infection rates were lower in counties where cell phone activity declined at workplaces and increased at home
A new study examines technological, socioeconomic and geopolitical forces altering the marketing industry — including deepening consumer relationships — and the implications for marketing managers, educators and researchers.
Every major medical center in America sits on a gold mine of patient data that could be worth millions of dollars to companies that could use it to develop new treatments and technologies. A new framework could help them do so more responsibly, going beyond the minimum legal requirements and respecting patients by giving them more say in how their individual data may be used.
Researchers who have parsed minimum-wage increases over the past half-decade find a mixed bag of immediate results in states that push wages higher, but the pandemic-roiled economy changes all that, they say.
ISPOR concluded its Virtual ISPOR 2020 conference yesterday—its first completely virtual conference. The conference was redesigned as an online event when the COVID-19 pandemic required a necessary cancellation of the in-person conference.
Researchers at Columbia Engineering and the University of South Carolina have developed a method that combines big data and machine learning to selectively design gas-filtering polymer membranes to reduce greenhouse gas emissions. Their study, published today in Science Advances, is the first to apply an experimentally validated machine learning method to rapidly design and develop advanced gas separation membranes.
The Deep Underground Neutrino Experiment will collect massive amounts of data from star-born and terrestrial neutrinos. A worldwide network of computers will provide the infrastructure to help analyze it. Using artificial intelligence and machine learning, scientists write software to mine the data.
For an experiment that will generate big data at unprecedented rates, physicists led design, development, mass production and delivery of an upgrade of novel particle detectors and state-of-the art electronics.
ISPOR—The Professional Society for Health Economics and Outcomes Research (HEOR) announced today the program and speakers for Virtual ISPOR 2020.
As part of the nation’s record $2 trillion relief bill, Congress has set aside $500 million for the CDC to develop a “public health surveillance and data collection system” meant to track the spread of coronavirus. While it’s not clear…
To better understand early signs of coronavirus and the virus’ spread, physicians around the country and data scientists at UC San Diego are working together to use a wearable device to monitor more than 12,000 people, including thousands of healthcare workers. The effort has started at hospitals in the San Francisco Bay Area and at the University of West Virginia.
A method of predicting the coronavirus spread – pioneered and developed by Weizmann Institute scientists – may enable authorities to focus efforts on areas where an outbreak is anticipated and relieve measures taken in others. Several countries, including the U.S., are adopting the new method
Your doctor protects your sensitive health data. But in a new publication, experts assert it’s important to check if that app you just downloaded will, too.
Sepsis causes nearly 270,000 deaths in the United States each year. Find out how big data approaches are helping clinicians catch it sooner, treat it better, and help survivors cope with long-term effects.
The Center for Space Plasma and Aeronomic Research (CSPAR) at The University of Alabama in Huntsville (UAH) will be central to the modeling and data crunching that follow the scheduled launch of NASA’s Interstellar Mapping and Acceleration Probe (IMAP) mission in 2024.
The University of Alabama in Huntsville (UAH) will have a major role in exploring an expected massive data stream that will follow the launch of the European Space Agency (ESA) Solar Orbiter, a mission that will fly over the sun’s poles and on which UAH’s Dr. Gary Zank is a co-primary investigator.
With a team of experts in fields including data science, statistics, computer science, finance, energy, agriculture, ecology, hydrology, climate and space weather, The Predictive Risk Investigation System for Multilayer Dynamic Interconnection Analysis (PRISM), funded by the National Science Foundation (NSF), will integrate data across different areas to improve risk prediction.
University of California San Diego School of Medicine researchers created a new type of brain cancer model for glioblastoma using stem cells, CRISPR and gene sequencing.
Evaluating the effectiveness of therapies for neurodegenerative diseases is often difficult because each patient’s progression is different. A new study shows artificial intelligence (AI) analysis of blood samples can predict and explain disease progression, which could one day help doctors choose more appropriate and effective treatments for patients.
A team of researchers from the National University of Singapore has developed a personalised assessment tool which can detect the incidence of cancer, predict patient survivability and determine patient suitability for immunotherapy cancer treatment.
British Petroleum researchers invited ORNL data scientists to give the company’s high-performance computing team a tutorial of the laboratory’s ADIOS I/O middleware. ADIOS has helped researchers achieve scientific breakthroughs by providing a simple, flexible way to describe data in their code that may need to be written, read, or processed outside of the running simulation. ORNL researchers Scott Klasky and Norbert Podhorszki demonstrated how it could help the BP team accelerate their science by helping tackle their large, unique seismic datasets.
ISPOR, the professional society for health economics and outcomes research—held its third plenary session at ISPOR Europe 2019, “Big Data Healthcare: Endless Opportunities for Research and Learning,” this morning.
What can reading 26,000 books tell researchers about how language environment affects language behavior? Brendan T. Johns, an assistant professor of communicative disorders and sciences at UB has published a computational modeling study that suggests our experience and interaction with specific learning environments, like the characteristics of what we read, leads to differences in language behavior that were once attributed to differences in cognition.
ISPOR—the professional society for health economics and outcomes research—will begin its ISPOR Europe 2019 2-6 November 2019 in Copenhagen, Denmark.
As part of the Department of Energy’s role in the fight against cancer, scientists are building tools that use supercomputers to solve problems in entirely new ways.
The American Academy of Ophthalmology (the Academy) and Research to Prevent Blindness (RPB) today announced this year’s recipients of the Research to Prevent Blindness/American Academy of Ophthalmology Award for IRIS® Registry Research. The grant supports researchers who want to conduct big data research in ophthalmology and blindness prevention.