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.

Preview

PDF 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

Request Changes to record.

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
Subjects:	Q Science > QA Mathematics Q Science > QH Natural history Q Science > QP Physiology R Medicine > RC Internal medicine
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:	Date Event 10 March 2022 Published 9 February 2022 Accepted
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:	Project/Grant ID RIOXX Funder Name Funder ID EP/V025899/1 [EPSRC] Engineering and Physical Sciences Research Council http://dx.doi.org/10.13039/501100000266 EP/T017112/1 [EPSRC] Engineering and Physical Sciences Research Council http://dx.doi.org/10.13039/501100000266 NE/T00973X/1 [NERC] Natural Environment Research Council http://dx.doi.org/10.13039/501100000270 823712 (CompBioMed2 project) Horizon 2020 Framework Programme http://dx.doi.org/10.13039/100010661 UNSPECIFIED ISPPC - CHU De Charleroi https://www.isppc.be/ UNSPECIFIED Fonds de la Chirurgie Cardiaque http://www.hart-chirurgie-cardiaque.org/ UNSPECIFIED Fonds pour la Recherche Me´dicale en Hainaut https://web.umons.ac.be/frmh/fr/

Request changes or add full text files to a record

Repository staff actions (login required)

View Item

Downloads