Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Chun Fung Kwok"'
Autor:
Helen M. L. Frazer, Carlos A. Peña-Solorzano, Chun Fung Kwok, Michael S. Elliott, Yuanhong Chen, Chong Wang, The BRAIx Team, Jocelyn F. Lippey, John L. Hopper, Peter Brotchie, Gustavo Carneiro, Davis J. McCarthy
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-12 (2024)
Abstract Artificial intelligence (AI) readers of mammograms compare favourably to individual radiologists in detecting breast cancer. However, AI readers cannot perform at the level of multi-reader systems used by screening programs in countries such
Externí odkaz:
https://doaj.org/article/2c201c5f842d4cf6b4d53d6962a08a8c
Publikováno v:
Atmosphere, Vol 14, Iss 2, p 193 (2023)
In this paper, we study the problem of extracting trends from time series data involving missing values. In particular, we investigate a general class of procedures that impute the missing data and then extract trends using seasonal-trend decompositi
Externí odkaz:
https://doaj.org/article/ee02d54efbdf4b27985453e86b4d5710
Autor:
Helen M. L. Frazer, Jennifer S. N. Tang, Michael S. Elliott, Katrina M. Kunicki, Brendan Hill, Ravishankar Karthik, Chun Fung Kwok, Carlos A. Peña-Solorzano, Yuanhong Chen, Chong Wang, Osamah Al-Qershi, Samantha K. Fox, Shuai Li, Enes Makalic, Tuong L. Nguyen, Daniel F. Schmidt, Prabhathi Basnayake Ralalage, Jocelyn F. Lippey, Peter Brotchie, John L. Hopper, Gustavo Carneiro, Davis J. McCarthy
Publikováno v:
Radiology: Artificial Intelligence. 5
BackgroundArtificial intelligence (AI) readers, derived from applying deep learning models to medical image analysis, hold great promise for improving population breast cancer screening. However, previous evaluations of AI readers for breast cancer s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c554553323a38a7797dcaa986e45ed35
https://doi.org/10.1101/2022.11.23.22282646
https://doi.org/10.1101/2022.11.23.22282646
Publikováno v:
SSRN Electronic Journal.
Automatic differentiation (AD) is a general method of computing exact derivatives in complex sensitivity analyses and optimisation routines in settings that lack closed-form solutions, thus posing challenges for analytical and numerical alternatives.
Autor:
Enrique Calderín-Ojeda, Chun Fung Kwok
Publikováno v:
Scandinavian Actuarial Journal. 2016:817-836
In this paper, a new class of composite model is proposed for modeling actuarial claims data of mixed sizes. The model is developed using the Stoppa distribution and a mode-matching procedure. The use of the Stoppa distribution allows for more flexib
Autor:
Mark S. Joshi, Chun Fung Kwok
Publikováno v:
SSRN Electronic Journal.
Variations of the binomial tree model are reviewed and extensions to the two most efficient trees studied in a recent literature are proposed. Tian’s modified tree is extended to a more general class of tree, and the third order tree is extended to
Autor:
Jacobi, Liana1 (AUTHOR) ljacobi@unimelb.edu.au, Kwok, Chun Fung1 (AUTHOR) kwokcf@unimelb.edu.au, Ramírez-Hassan, Andrés2 (AUTHOR) aramir21@eafit.edu.co, Nghiem, Nhung3 (AUTHOR) nhung.nghiem@otago.ac.nz
Publikováno v:
Studies in Nonlinear Dynamics & Econometrics. Apr2024, Vol. 28 Issue 2, p403-434. 32p.
Autor:
Frazer, Helen M. L., Peña-Solorzano, Carlos A., Kwok, Chun Fung, Elliott, Michael S., Chen, Yuanhong, Wang, Chong, Al-Qershi, Osamah, Fox, Samantha K., Hill, Brendan, Karthik, Ravishankar, Kunicki, Katrina, Li, Shuai, Makalic, Enes, Nguyen, Tuong L., Ralalage, Prabhathi Basnayake, Schmidt, Daniel, Weideman, Prue C., Lippey, Jocelyn F., Hopper, John L., Brotchie, Peter
Publikováno v:
Nature Communications; 9/2/2024, Vol. 15 Issue 1, p1-12, 12p
Publikováno v:
Atmosphere; Feb2023, Vol. 14 Issue 2, p193, 21p