Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Theodora S. Brisimi"'
Autor:
Theodora S. Brisimi, Christos G. Cassandras, Chris Osgood, Ioannis CH. Paschalidis, Yue Zhang
Publikováno v:
IEEE Access, Vol 4, Pp 1301-1312 (2016)
We develop an infrastructure-free approach for anomaly detection and identification based on data collected through a smartphone application (Street Bump). The approach is capable of effectively classifying roadway obstacles into predefined categorie
Externí odkaz:
https://doaj.org/article/3e8b1052f5e24343a414c6cc6ecc3829
Autor:
Theodora S, Brisimi, Vanessa, Lopez, Valentina, Rho, Marco, Sbodio, Gabriele, Picco, Morten, Kristiansen, John, Segrave-Daly, Conor, Cullen
Publikováno v:
Studies in health technology and informatics. 270
Financial losses in Medicaid, from Fraud, Waste and Abuse (FWA), in the United States are estimated to be in the tens of billions of dollars each year. This results in escalating costs as well as limiting the funding available to worthy recipients of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::61cc9981bb239d357c63c1afcff532a8
https://pubmed.ncbi.nlm.nih.gov/32570508
https://pubmed.ncbi.nlm.nih.gov/32570508
Autor:
Theodora S. Brisimi, Theofanie Mela, Ioannis Ch. Paschalidis, Alex Olshevsky, Wei Shi, Ruidi Chen
Publikováno v:
International Journal of Medical Informatics. 112:59-67
Background In an era of “big data,” computationally efficient and privacy-aware solutions for large-scale machine learning problems become crucial, especially in the healthcare domain, where large amounts of data are stored in different locations
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::89f130191b09ef6dccb64b79fbb41e07
https://doi.org/10.1016/j.ijmedinf.2018.01.007
https://doi.org/10.1016/j.ijmedinf.2018.01.007
Autor:
Tingting Xu, Ioannis Ch. Paschalidis, Wuyang Dai, Theodora S. Brisimi, William G. Adams, Taiyao Wang
Publikováno v:
Proceedings of the IEEE. 106:690-707
Urban living in modern large cities has significant adverse effects on health, increasing the risk of several chronic diseases. We focus on the two leading clusters of chronic diseases, heart disease and diabetes, and develop data-driven methods to p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::073845a66cc62b9a5f9915ed31a1a66d
https://doi.org/10.1109/jproc.2017.2789319
https://doi.org/10.1109/jproc.2017.2789319
Publikováno v:
European Journal of Operational Research. 250:262-272
In this study, we developed a DEA-based performance measurement methodology that is consistent with performance assessment frameworks such as the Balanced Scorecard. The methodology developed in this paper takes into account the direct or inverse rel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e920daa551f1ae542530670e99c96d42
https://doi.org/10.1016/j.ejor.2015.08.055
https://doi.org/10.1016/j.ejor.2015.08.055
Autor:
Jillian Scalvini, Valentina Rho, Fabrizio Cucci, Theodora S. Brisimi, Vanessa Lopez, John Segrave-Daly, Grace Ferguson, Morten Kristiansen, John Davis
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030307950
ISWC (2)
ISWC (2)
With healthcare fraud accounting for financial losses of billions of dollars each year in the United States, the task of investigating regulation adherence is key to reduce the impact of Fraud, Waste and Abuse (FWA) on the healthcare industry. Provid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bd8da74e129ba7109fdea682190deee1
https://doi.org/10.1007/978-3-030-30796-7_29
https://doi.org/10.1007/978-3-030-30796-7_29
Publikováno v:
Stat Methods Med Res
Objective: To derive a predictive model to identify patients likely to be hospitalized during the following year due to complications attributed to Type II diabetes. Methods: A variety of supervised machine learning classification methods were tested
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ec7fe61660a2fe6ca471e0cb55c2d1d
https://pubmed.ncbi.nlm.nih.gov/30474497
https://pubmed.ncbi.nlm.nih.gov/30474497
Autor:
Chris Osgood, Christos G. Cassandras, Theodora S. Brisimi, Yue Zhang, Ioannis Ch. Paschalidis
Publikováno v:
IEEE Access, Vol 4, Pp 1301-1312 (2016)
We develop an infrastructure-free approach for anomaly detection and identification based on data collected through a smartphone application (Street Bump). The approach is capable of effectively classifying roadway obstacles into predefined categorie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c7f38d244afec38b934fd289fdba097c
https://doi.org/10.1109/access.2016.2529562
https://doi.org/10.1109/access.2016.2529562
Autor:
Christos G. Cassandras, Setareh Ariafar, Ioannis Ch. Paschalidis, Theodora S. Brisimi, Yue Zhang
Publikováno v:
CASE
We develop an anomaly detection and decision support system based on data collected through the Street Bump smartphone application. The system is capable of effectively classifying roadway obstacles into predefined categories using machine learning a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aa377bddc7eead671eafb8c735901955
https://doi.org/10.1109/coase.2015.7294276
https://doi.org/10.1109/coase.2015.7294276
Autor:
Wuyang Dai, Ioannis Ch. Paschalidis, William G. Adams, Theofanie Mela, Venkatesh Saligrama, Theodora S. Brisimi
Background In 2008, the United States spent $2.2 trillion for healthcare, which was 15.5% of its GDP. 31% of this expenditure is attributed to hospital care. Evidently, even modest reductions in hospital care costs matter. A 2009 study showed that ne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::de87c30138add2defcb34e5948933432
https://europepmc.org/articles/PMC4314395/
https://europepmc.org/articles/PMC4314395/