Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Paul Fearn"'
Publikováno v:
In Computers & Security March 2012 31(2):206-220
Autor:
Vincent Runge, Toby Dylan Hocking, Gaetano Romano, Fatemeh Afghah, Paul Fearnhead, Guillem Rigaill
Publikováno v:
Journal of Statistical Software, Vol 106, Pp 1-39 (2023)
In a world with data that change rapidly and abruptly, it is important to detect those changes accurately. In this paper we describe an R package implementing a generalized version of an algorithm recently proposed by Hocking, Rigaill, Fearnhead, and
Externí odkaz:
https://doaj.org/article/e67e85b988e8481c9b7a577d7dff285d
Autor:
Giuseppe Dilillo, Kes Ward, Idris A. Eckley, Paul Fearnhead, Riccardo Crupi, Yuri Evangelista, Andrea Vacchi, Fabrizio Fiore
Publikováno v:
The Astrophysical Journal, Vol 962, Iss 2, p 137 (2024)
We describe how a novel online change-point detection algorithm, called Poisson-FOCuS, can be used to optimally detect gamma-ray bursts within the computational constraints imposed by miniaturized satellites such as the upcoming HERMES-Pathfinder con
Externí odkaz:
https://doaj.org/article/e8116116bb3e4169bdb04c661e91bcd6
Publikováno v:
Computers & Security. 31:206-220
Using Reason's GEMS typology to analyze publicly available reports of privacy breaches in the United States shows human error as the cause of a significant number of violations of HIPAA Privacy Rule. An interpretive study based on interviews of 15 pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::85fc9f57b6760fc89adad83784494af8
https://doi.org/10.1016/j.cose.2011.12.002
https://doi.org/10.1016/j.cose.2011.12.002
Autor:
Christopher S. Foster, Caroline O. S. Savage, R. Timothy D. Oliver, Daniel M. Berney, James A. Eastham, Jack Cuzick, M. Frank O'Brien, Andrew J. Vickers, Paul Fearn, Hans Lilja, Angel M. Cronin, Jason Stasi, Gabrielle Fisher, Brandon Smith, Peter T. Scardino, Henrik Møller
Publikováno v:
International Journal of Cancer. 128:2373-2381
Prostate-specific antigen (PSA) dynamics have been proposed to predict outcome in men with prostate cancer. We assessed the value of PSA velocity (PSAV) and PSA doubling time (PSADT) for predicting prostate cancer-specific mortality (PCSM) in men wit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a5af415b8d7fcddeb20d6504dc42b6d
https://doi.org/10.1002/ijc.25570
https://doi.org/10.1002/ijc.25570
Autor:
Peter T. Scardino, James A. Eastham, A B A Paul Fearn, Victor Reuter, Thomas M. Wheeler, Fernando J. Bianco, Fernando P. Secin, Andrew J. Vickers
Publikováno v:
Cancer. 106:2369-2375
BACKGROUND The objectives of the current study were to determine the long-term biochemical recurrence (BCR) and cancer-specific survival (CSS) rates for men with seminal vesicle invasion (SVI) and to identify risk factors for freedom from BCR and CSS
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9429d0458c5eaad0e2ded1999d68942a
https://doi.org/10.1002/cncr.21895
https://doi.org/10.1002/cncr.21895
Publikováno v:
Biopreservation and Biobanking. 11:64-66
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b44c07a3c2cf272d783f782fa1254275
https://doi.org/10.1089/bio.2012.1115
https://doi.org/10.1089/bio.2012.1115
Publikováno v:
Journal of Statistical Software, Vol 101, Pp 1-31 (2022)
We describe a new algorithm and R package for peak detection in genomic data sets using constrained changepoint models. These detect changes from background to peak regions by imposing the constraint that the mean should alternately increase then dec
Externí odkaz:
https://doaj.org/article/01c9f7e6dfcd4f27836ce98edc88d868
Publikováno v:
Science Translational Medicine. 4
A set of principles is proposed for sponsors and developers of research computing applications that can increase the likelihood of successful adoption by researchers.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::059ac89b9a3d7df82ccc8e87c16ca8b2
https://doi.org/10.1126/scitranslmed.3004032
https://doi.org/10.1126/scitranslmed.3004032
Autor:
Frank Sculli, Paul Fearn
Publikováno v:
Biomedical Informatics for Cancer Research ISBN: 9781441957122
CAISIS is a research data system that was started to support predictive model development in urologic oncology at Memorial Sloan-Kettering Cancer Center (MSKCC) and has become widely adopted across different departments and institutions to manage bio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bcdd47653430374026bcb44c21c0dbc4
https://doi.org/10.1007/978-1-4419-5714-6_11
https://doi.org/10.1007/978-1-4419-5714-6_11
