Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Sait, Tunc"'
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-14 (2022)
Abstract As new COVID-19 variants emerge, and disease and population characteristics change, screening strategies may also need to change. We develop a decision-making model that can assist a college to determine an optimal screening strategy based o
Externí odkaz:
https://doaj.org/article/4fa2eeda16fd4dc19871aee7a85bedb8
Publikováno v:
PLoS ONE, Vol 17, Iss 4 (2022)
Importance Screening and vaccination are essential in the fight against infectious diseases, but need to be integrated and customized based on community and disease characteristics. Objective To develop effective screening and vaccination strategies,
Externí odkaz:
https://doaj.org/article/11b2e385d55c44ea8ca5baa52375ec0b
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-1 (2022)
Externí odkaz:
https://doaj.org/article/baeb29e86179499f97c977703377ca5a
Publikováno v:
Management Science. 68:5980-6002
Despite efforts to increase the supply of donated organs for transplantation, organ shortages persist. We study the problem of organ wastage in a queueing-theoretic framework. We establish that self-interested individuals set their utilization levels
Overdiagnosis of breast cancer, defined as diagnosing a cancer that would otherwise not cause symptoms or death in a patient's lifetime, costs U.S. health care system over $1.2 billion annually. Overdiagnosis rates, estimated to be around 10%-40%, ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2c2d5ae46fbfb343951d163c3087b924
https://hdl.handle.net/10919/111244
https://hdl.handle.net/10919/111244
Publikováno v:
WSC
The United Network for Organ Sharing (UNOS) has been using simulation models for over two decades to guide the evolution of organ allocation policies in the United States. UNOS kidney simulation model (KPSAM), which played a crucial role in the 2014
Publikováno v:
Decision Analytics and Optimization in Disease Prevention and Treatment
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::80f1cdf5169ca5701b5fb7c4fa916e83
https://doi.org/10.1002/9781118960158.ch8
https://doi.org/10.1002/9781118960158.ch8
Publikováno v:
Digital Signal Processing: A Review Journal
Achieving optimal expected growth in i.i.d. discrete-time markets.Efficient recursive calculation via an irreducible Markov chain formulation.Successful application to Brownian markets and historical data. We investigate how and when to diversify cap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3c31047b7533b366066219fd7e12078
https://hdl.handle.net/11693/36852
https://hdl.handle.net/11693/36852
Publikováno v:
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks and Learning Systems
IEEE Transactions on Neural Networks and Learning Systems
We analyze an online learning algorithm that adaptively combines outputs of two constituent algorithms (or the experts) running in parallel to model an unknown desired signal. This online learning algorithm is shown to achieve (and in some cases outp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::818a1424a7cbbec994bc00ed21ef7dea
https://hdl.handle.net/11693/12548
https://hdl.handle.net/11693/12548
Autor:
Hui Yang, Erhun Kundakcioglu, Jing Li, Teresa Wu, J. Ross Mitchell, Amy K. Hara, William Pavlicek, Leland S. Hu, Alvin C. Silva, Christine M. Zwart, Sait Tunc, Oguzhan Alagoz, Elizabeth Burnside, W. Art Chaovalitwongse, Georgiy Presnyakov, Yulian Cao, Sirirat Sujitnapitsatham, Daehan Won, Tara Madhyastha, Kurt E. Weaver, Paul R. Borghesani, Thomas J. Grabowski, Lianjie Shu, Man Ho Ling, Shui-Yee Wong, Kwok-Leung Tsui
Due to copyright restrictions, the access to the full text of this article is only available via subscription. Exceptional opportunities exist for researchers and practitioners to invest in conducting innovative and transformative research in data mi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::40cfe16bad30b7d020e1e66e30faa920
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6871721
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6871721