| Literature DB >> 32674794 |
Thomas A Pearson1, Robert M Califf2, Rebecca Roper3, Michael M Engelgau3, Muin J Khoury4, Carmela Alcantara5, Craig Blakely6, Cheryl Anne Boyce3, Marishka Brown7, Thomas L Croxton7, Kathleen Fenton3, Melissa C Green Parker3, Andrew Hamilton8, Lorens Helmchen9, Lucy L Hsu10, David M Kent11, Amy Kind12, John Kravitz13, George John Papanicolaou10, Mattia Prosperi14, Matt Quinn15, LeShawndra N Price3, Paula K Shireman16, Sharon M Smith17, Rhonda Szczesniak18, David Calvin Goff10, George A Mensah19.
Abstract
Emerging data science techniques of predictive analytics expand the quality and quantity of complex data relevant to human health and provide opportunities for understanding and control of conditions such as heart, lung, blood, and sleep disorders. To realize these opportunities, the information sources, the data science tools that use the information, and the application of resulting analytics to health and health care issues will require implementation research methods to define benefits, harms, reach, and sustainability; and to understand related resource utilization implications to inform policymakers. This JACC State-of-the-Art Review is based on a workshop convened by the National Heart, Lung, and Blood Institute to explore predictive analytics in the context of implementation science. It highlights precision medicine and precision public health as complementary and compelling applications of predictive analytics, and addresses future research and training endeavors that might further foster the application of predictive analytics in clinical medicine and public health.Entities:
Keywords: exposome; genome; implementation research; predictive analytics; social determinants
Year: 2020 PMID: 32674794 DOI: 10.1016/j.jacc.2020.05.043
Source DB: PubMed Journal: J Am Coll Cardiol ISSN: 0735-1097 Impact factor: 24.094