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Hybrid machine learning approaches in viability assessment of dental pulp stem cells treated with platelet-rich concentrates on different periods

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Bindal, P, Bindal, U, Kazemipoor, M, Kazemipoor, M and Jha, SK 2019 , 'Hybrid machine learning approaches in viability assessment of dental pulp stem cells treated with platelet-rich concentrates on different periods' , Applied Medical Informatics, vol. 41, no. 3 , pp. 93-101 .

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Abstract

The unique characteristics of dental pulp stem cells (DPSCs), like multi-lineage differentiation, haveattracted considerable interest among clinicians and researchers for the treatment of various diseases.Platelet-derived concentrates (PRSs) are utilized for wound healing, due to the plethora of growthfactors that are released from platelets. In this study, DPSCs were cultured with one of the threeculture supplements, including fetal bovine serum (FBS), human platelet-rich plasma (PRP), andhuman platelet lysate (HPL). The viability effects of these platelet-derived culture supplements onDPSCs were evaluated using hybrid approaches of fuzzy-genetic methods. The results showed thatDPSCs cultured in HPL have higher viability than FBS and PRP. It is suggested that fuzzy-geneticalgorithm (GA) is an accurate approach to estimate the effect of platelet concentrates on theproliferation of stem cells derived from the human tooth.

Item Type: Article
Authors/Creators:Bindal, P and Bindal, U and Kazemipoor, M and Kazemipoor, M and Jha, SK
Keywords: stem cells, AI, human platelet-rich concentrates, fuzzy-genetic algorithm
Journal or Publication Title: Applied Medical Informatics
Publisher: Romanian Society of Applied Medical Informatics (S R I M A)
ISSN: 1224-5593
Copyright Information:

Copyright 2019 The Authors. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/

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