Zobrazeno 1 - 10
of 105
pro vyhledávání: '"Hadley, Emily"'
Organizations including companies, nonprofits, governments, and academic institutions are increasingly developing, deploying, and utilizing artificial intelligence (AI) tools. Responsible AI (RAI) governance approaches at organizations have emerged a
Externí odkaz:
http://arxiv.org/abs/2402.01691
Autor:
Hadley, Emily
Several policy options exist, or have been proposed, to further responsible artificial intelligence (AI) development and deployment. Institutions, including U.S. government agencies, states, professional societies, and private and public sector busin
Externí odkaz:
http://arxiv.org/abs/2212.00740
Autor:
Jones, Kasey, Preiss, Alexander, Hadley, Emily, Rhea, Sarah, Kery, Caroline, Stoner, Marie C. D., Adams, Joëlla W.
This Overview, Design Concepts, and Details (ODD) Protocol is an ODD extension to an agent-based model (ABM) framework built for the North Carolina Modeling Infectious Diseases Program (NC MInD). The model, NC MInD ABM, can be used as a base model fo
Externí odkaz:
http://arxiv.org/abs/2202.09243
Autor:
Jones, Kasey, Hadley, Emily, Kery, Caroline, Preiss, Alexander, Stoner, Marie C. D., Rhea, Sarah
To help facilitate a variety of simulations related to healthcare facilities in North Carolina, we have developed an agent-based model (ABM) to accurately simulate patient (i.e., agent) movement to and from these facilities. This is an Overview, Desi
Externí odkaz:
http://arxiv.org/abs/2202.06853
Publikováno v:
Journal of Data Science. Jul2024, Vol. 22 Issue 3, p393-408. 16p.
Autor:
Jones, Kasey, Hadley, Emily, Preiss, Sandy, Kery, Caroline, Baumgartner, Peter, Stoner, Marie, Rhea, Sarah
This Overview, Design Concepts, and Details Protocol (ODD) provides a detailed description of an agent-based model (ABM) that was developed to simulate hospitalizations during the COVID-19 pandemic. Using the descriptions of submodels, provided param
Externí odkaz:
http://arxiv.org/abs/2106.04461
Autor:
Chew, Rob, Wenger, Michael, Kery, Caroline, Nance, Jason, Richards, Keith, Hadley, Emily, Baumgartner, Peter
Publikováno v:
The Journal of Machine Learning Research, 20(1), 2999-3003 (2019)
SMART is an open source web application designed to help data scientists and research teams efficiently build labeled training data sets for supervised machine learning tasks. SMART provides users with an intuitive interface for creating labeled data
Externí odkaz:
http://arxiv.org/abs/1812.06591
Publikováno v:
Contemporary Drug Problems; December 2024, Vol. 51 Issue: 4 p318-333, 16p
Autor:
Preiss, Alexander1 apreiss@rti.org, Hadley, Emily1, Jones, Kasey1, Stoner, Marie C. D.1, Kery, Caroline1, Baumgartner, Peter2, Bobashev, Georgiy1, Tenenbaum, Jessica3, Carter, Charles3, Clement, Kimberly3, Rhea, Sarah4
Publikováno v:
Infectious Disease Modelling (2468-2152). Mar2022, Vol. 7 Issue 1, p277-285. 9p.
Autor:
Hadley, Emily1 (AUTHOR) ehadley@rti.org, Rhea, Sarah1,2 (AUTHOR), Jones, Kasey1 (AUTHOR), Li, Lei1 (AUTHOR), Stoner, Marie1 (AUTHOR), Bobashev, Georgiy1 (AUTHOR)
Publikováno v:
PLoS ONE. 3/1/2022, Vol. 17 Issue 3, p1-11. 11p.