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Validating and improving serum biomarkers for liver cancer surveillance
King, Ruth
(Principal Investigator)
Bird, Tom
(Co-investigator)
Calhau Fernandes Inacio De Carvalho, Vanda
(Co-investigator)
School of Mathematics
School of Regeneration and Repair
Bayes Centre
Overview
Fingerprint
Research output
(1)
Project Details
Status
Finished
Effective start/end date
1/09/18
→
28/02/19
Funding
UK-based charities:
£15,500.00
View all
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Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
Hidden Markov Models
Mathematics
100%
Continuous Time
Mathematics
100%
Hidden Markov Model
Immunology and Microbiology
100%
False Negative
Mathematics
50%
Bayesian
Mathematics
50%
Cutoff Point
Mathematics
50%
Longitudinal Data
Mathematics
50%
Hierarchical Model
Mathematics
50%
Research output
Research output per year
2019
2019
2019
1
Article
Research output per year
Research output per year
A continuous-time hidden Markov model for cancer surveillance using serum biomarkers with application to hepatocellular carcinoma
Amoros Salvador, R.,
King, R.
, Toyoda, H., Kumada, T., Johnson, P. J. &
Bird, T. G.
,
31 Aug 2019
,
In:
METRON.
77
,
2
,
p. 67-86
20 p.
Research output
:
Contribution to journal
›
Article
›
peer-review
Open Access
File
Hidden Markov Models
100%
Continuous Time
100%
Hidden Markov Model
100%
Bayesian
50%
Cutoff Point
50%