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Personalized pathology test for Cardio-vascular disease : approximate Bayesian computation with discriminative summary statistics learning
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Dutta, Ritabrata, Zouaoui Boudjeltia, Karim, Kotsalos, Christos, Rousseau, Alexandre, Ribeiro de Sousa, Daniel, Desmet, Jean-Marc, Van Meerhaeghe, Alain, Mira, Antonietta and Chopard, Bastien (2022) Personalized pathology test for Cardio-vascular disease : approximate Bayesian computation with discriminative summary statistics learning. PLoS Computational Biology, 18 (3). e1009910. doi:10.1371/journal.pcbi.1009910 ISSN 1553-7358.
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WRAP-personalized-pathology-test-Cardio-vascular-disease-Dutta-2022.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (3504Kb) | Preview |
Official URL: http://dx.doi.org/10.1371/journal.pcbi.1009910
Abstract
Cardio/cerebrovascular diseases (CVD) have become one of the major health issue in our societies. But recent studies show that the present pathology tests to detect CVD are ineffectual as they do not consider different stages of platelet activation or the molecular dynamics involved in platelet interactions and are incapable to consider inter-individual variability. Here we propose a stochastic platelet deposition model and an inferential scheme to estimate the biologically meaningful model parameters using approximate Bayesian computation with a summary statistic that maximally discriminates between different types of patients. Inferred parameters from data collected on healthy volunteers and different patient types help us to identify specific biological parameters and hence biological reasoning behind the dysfunction for each type of patients. This work opens up an unprecedented opportunity of personalized pathology test for CVD detection and medical treatment.
Item Type: | Journal Article | ||||||||||||||||||||||||
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Subjects: | Q Science > QA Mathematics Q Science > QH Natural history Q Science > QP Physiology R Medicine > RC Internal medicine |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||||||||||||||||||||
Library of Congress Subject Headings (LCSH): | Cardiovascular system -- Diseases , Cardiovascular system -- Diseases -- Diagnosis -- Testing, Cardiovascular system -- Diseases -- Diagnosis -- Statistical methods, Bayesian statistical decision theory , Computational biology , Blood platelets | ||||||||||||||||||||||||
Journal or Publication Title: | PLoS Computational Biology | ||||||||||||||||||||||||
Publisher: | Public Library of Science | ||||||||||||||||||||||||
ISSN: | 1553-7358 | ||||||||||||||||||||||||
Official Date: | 10 March 2022 | ||||||||||||||||||||||||
Dates: |
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Volume: | 18 | ||||||||||||||||||||||||
Number: | 3 | ||||||||||||||||||||||||
Article Number: | e1009910 | ||||||||||||||||||||||||
DOI: | 10.1371/journal.pcbi.1009910 | ||||||||||||||||||||||||
Status: | Peer Reviewed | ||||||||||||||||||||||||
Publication Status: | Published | ||||||||||||||||||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||||||||||||||||||
Date of first compliant deposit: | 14 April 2022 | ||||||||||||||||||||||||
Date of first compliant Open Access: | 19 April 2022 | ||||||||||||||||||||||||
RIOXX Funder/Project Grant: |
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