Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Yura Perov"'
Autor:
Yuanzhao Zhang, Robert Walecki, Joanne R. Winter, Felix J. S. Bragman, Sara Lourenco, Christopher Hart, Adam Baker, Yura Perov, Saurabh Johri
Publikováno v:
Frontiers in Digital Health, Vol 2 (2020)
Background: AI-driven digital health tools often rely on estimates of disease incidence or prevalence, but obtaining these estimates is costly and time-consuming. We explored the use of machine learning models that leverage contextual information abo
Externí odkaz:
https://doaj.org/article/5a40111c5bf440f5b050c37761d75fce
Autor:
Adam Baker, Yura Perov, Katherine Middleton, Janie Baxter, Daniel Mullarkey, Davinder Sangar, Mobasher Butt, Arnold DoRosario, Saurabh Johri
Publikováno v:
Frontiers in Artificial Intelligence, Vol 3 (2020)
AI virtual assistants have significant potential to alleviate the pressure on overly burdened healthcare systems by enabling patients to self-assess their symptoms and to seek further care when appropriate. For these systems to make a meaningful cont
Externí odkaz:
https://doaj.org/article/825ca61f0ed94061b1c92aad7079f6de
Autor:
Robert Walecki, Christopher Hart, Sara Lourenco, Saurabh Johri, Adam Baker, Felix J. S. Bragman, Joanne R. Winter, Yuanzhao Zhang, Yura Perov
Publikováno v:
Frontiers in Digital Health, Vol 2 (2020)
Frontiers in Digital Health
Frontiers in Digital Health
Background: AI-driven digital health tools often rely on estimates of disease incidence or prevalence, but obtaining these estimates is costly and time-consuming. We explored the use of machine learning models that leverage contextual information abo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::993ee949f64f321c1db72fb573384f75
https://www.frontiersin.org/articles/10.3389/fdgth.2020.569261/full
https://www.frontiersin.org/articles/10.3389/fdgth.2020.569261/full
Autor:
Arnold DoRosario, Daniel Mullarkey, Yura Perov, Katherine Middleton, Davinder Sangar, Janie Baxter, M.Z. Butt, Saurabh Johri, Adam Baker
Publikováno v:
Frontiers in Artificial Intelligence
Frontiers in Artificial Intelligence, Vol 3 (2020)
Frontiers in Artificial Intelligence, Vol 3 (2020)
AI virtual assistants have significant potential to alleviate the pressure on overly burdened healthcare systems by enabling patients to self-assess their symptoms and to seek further care when appropriate. For these systems to make a meaningful cont
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::523b74a0c25d93255f8d696644cd595c
http://europepmc.org/articles/PMC7861270
http://europepmc.org/articles/PMC7861270
Publikováno v:
IROS
Human locomotion and activity recognition systems form a critical part in a robot's ability to safely and effectively operate in a environment populated with human end users. Previous work in this area relies upon strong assumptions about the labels
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ad2bee1c783b5fc158c054d61523815
https://doi.org/10.1109/iros.2016.7759595
https://doi.org/10.1109/iros.2016.7759595
Autor:
Yura Perov, Frank Wood
Publikováno v:
Artificial General Intelligence ISBN: 9783319416489
AGI
AGI
We describe an approach to automatic discovery of samplers in the form of human interpretable probabilistic programs. Specifically, we learn the procedure code of samplers for one-dimensional distributions. We formulate a Bayesian approach to this pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b88d712a03e41d7690cf01554267d514
https://doi.org/10.1007/978-3-319-41649-6_27
https://doi.org/10.1007/978-3-319-41649-6_27
