20 hot topic(s) found with the query "Big data"
Using Digital Technologies in Precision Public Health: COVID-19 and Beyond
MJ Khoury et al, CDC Blog, April 2020
(Posted: Apr-26-2020 8AM)
With the global spread of COVID-19, there is a proliferation of scientific information and publications that use novel approaches such as genomics and precision health tools (e.g., big data, wearables, and digital devices) in surveillance and epidemiologic investigations. Could these new technologies provide added value to traditional approaches?
The Public Health Impact of COVID-19: Why Host Genomics?
MJ Khoury el al, CDC Blog, April 21, 2020
(Posted: Apr-22-2020 0PM)
Ideally, scientific studies of COVID-19 risk factors for transmission and severity should include both viral and human genomes and the interaction of these two genomes, along with other traditional environmental, social and economic factors, and emerging types of big data. This is part of a precision public health response.
Data Science and Machine Learning in Public Health: Promises and Challenges
C Patel et al, CDC Blog Post, September 20, 2019
(Posted: Sep-23-2019 8AM)
Big data include large amount of information becoming available to researchers. What makes them really “big” is the sheer number of individuals and/or the massive amount of information. Given that the primary use for these datasets is often not research, the question is, “are these data helpful for health-related discoveries and public health surveillance?”
Seeking More Precision in Public Health
K. Bibbins-Domingo CDC Seminar, October 22 at 1 pm.
(Posted: Sep-16-2019 9AM)
While precision medicine has made advances in individualized patient treatments, progress at the population level requires a public health approach focused on tailored population health and prevention strategies and driven by “big data” approaches. Inclusion of diverse populations and a focus on disparities reduction are key components.
Report: Dry AMD requires broad, systems biology approach leveraging big data, multiple disciplines
NIH News Release, July 26, 2019
(Posted: Jul-28-2019 4PM)
Can Big Data Science Deliver Precision Public Health?
MJ Khoury et al, CDC Blog Post, July 23, 2019
(Posted: Jul-24-2019 10AM)
In the age of big data, more extensive information by place, person and time are becoming available to measure public health impact and implementation needs. In principle, big data could point to implementation gaps and disparities and accelerate the evaluation of implementation strategies to reach population groups in most need for interventions. However, major challenges need to be overcome.
Assessing Gene-Environment Interactions in the Study of Rare Diseases
CDC Webinar, August 21, 2019
(Posted: Jun-28-2019 8AM)
The third installment of the 2019 CDC summer public health genomics seminar series. Sign up today to all three seminars, also available for viewing remotely and covering a wide range of topics from infectious disease, big data and rare diseases.
Genomics, Big Data and Data Science in Public Health
CDC Webinar, August 9, 2019
(Posted: Jun-28-2019 8AM)
Big Data Scientist Training Enhancement Program (BD-STEP)
(Posted: Jun-24-2019 8AM)
A two-year fellowship opportunity that uses data science to advance cancer research and care.
Bioinformatics, Big Data, and Cancer
NCI, March 2019
(Posted: Mar-31-2019 5PM)
Big Data to Knowledge Program Resources
(Posted: Jan-17-2019 8AM)
Creative Minds: Building Better Computational Models of Common Disease
NIH Director's Blog, Feb 8, 2018
(Posted: Feb-08-2018 10AM)
Health Disparities: Big Data to the Rescue?
F Wood, National Library of Medicine, May 16, 2017
(Posted: May-17-2017 7AM)
Cardiometabolic Disease: Big Data Tackles a Big Health Problem
Francis Collins, NIH Director Blog, September 8, 2016
(Posted: Sep-09-2016 11AM)
International Big Data Study Offers Fresh Insights into T2D
Francis Collins NIH director blog, July 12, 2016
(Posted: Jul-12-2016 2PM)
Big Data and the Promise and Pitfalls When Applied to Disease Prevention and Promoting Better Health
NIH Webinar, P Bourne, June 13, 2016
(Posted: May-24-2016 5PM)
Big data presents big challenges, big opportunities in environmental health
J Yewell, Environmental Factor, NIEHS August 2015
(Posted: Aug-19-2015 11AM)
NIH Data Science Portal: Enabling Biomedical Scientists to capitalize more fully on the Big Data being generated by the research communities
(Posted: Apr-14-2015 0PM)
Public health approach to big data in the age of genomics: How can we separate signal from noise?
(Posted: Feb-25-2015 0PM)
NCI-DOE Collaboration Paving Way for Large-Scale Computational Cancer Science
(Posted: Jan-11-2014 11AM)
Imagine the concentrated power of more than one million laptops working to screen a tumor sample from a patient against thousands of drugs and millions of drug combinations. At the end of this screening process, this mega-computer would help to identify a specific treatment with the greatest potential to combat that patient?s cancer.
NCI scientists, in collaboration with colleagues with the Department of Energy (DOE) Exascale Computing InitiativeExit Disclaimer (ECI) and the National Strategic Computing Initiative (NSCI), have been hard at work for the past 14 months developing a plan to use this type of large-scale computing to influence cancer science and, ultimately, clinical treatment.
In a unique interagency initiative, leading scientists from NCI and several national DOE laboratories have been developing plans for a pilot collaboration that would help both agencies by significantly expanding NCI?s research capabilities and simultaneously advancing DOE?s efforts to develop energy efficient Exascale computing solutions.
Exascale computing refers to a system with the capability of making a billion billion calculations per second?also known as an exaFLOPS. Exascale is being studied as a means of improving the design of advanced materials, reverse engineering the human brain, and designing cost-effective renewable energy resources, among many other applications.
NCI and DOE leaders believe something with such massive power to interrogate and decipher big data could play an important role in cancer research.
As our plans have progressed, so too has the enthusiasm about the opportunities this collaboration presents to deliver important scientific insights, advance strategic computing, and offer new research opportunities for cancer investigators worldwide.
Consistent with the goals of NCI?s Precision Medicine Initiative, as well as the previously announced NSCI, the pilot activities emphasize three key areas:
?Developing new computational approaches to support research being done under NCI?s RAS Initiative
?Using large-scale computation to accelerate the development of patient-derived laboratory models of cancer
?Better understanding the impact of existing therapies outside of clinical trials, in real-world practice.
Considered individually, each of these pilot activities has significant potential to help advance our understanding of cancer. But when integrated with NCI?s research expertise and vast data resources and DOE?s computational modeling and supercomputing expertise, they can create opportunities and lead to insights that could pay tremendous dividends for years to come.
Warren Kibbe, Ph.D. Director, NCI Center for Biomedical Informatics and Information Technology
Warren Kibbe, Ph.D.
Director, NCI Center for Biomedical Informatics and Information Technology
This unique collaboration will take advantage of NCI?s and DOE?s strengths, bringing together the remarkable power of supercomputing and the collective knowledge and wisdom of the cancer research community.
Through this collaboration, we?re beginning construction of the 21st century digital launchpad needed to conduct next-generation cancer research and providing a framework for the many future missions that will produce critical innovations in cancer treatment. In doing so, we?re hopeful that we can build upon the tremendous progress that?s been achieved by the nation?s consistent commitment to advancing cancer research. Cancer