Hybrid Machine Learning Approaches in Viability Assessment of Dental Pulp Stem Cells Treated with Platelet-Rich Concentrates on Different Periods

Abstract

The unique characteristics of dental pulp stem cells (DPSCs), like multi-lineage differentiation, have attracted 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 growth factors that are released from platelets. In this study, DPSCs were cultured with one of the three culture supplements, including fetal bovine serum (FBS), human platelet-rich plasma (PRP), and human platelet lysate (HPL). The viability effects of these platelet-derived culture supplements on DPSCs were evaluated using hybrid approaches of fuzzy-genetic methods. The results showed that DPSCs cultured in HPL have higher viability than FBS and PRP. It is suggested that fuzzy-genetic algorithm (GA) is an accurate approach to estimate the effect of platelet concentrates on the proliferation of stem cells derived from the human tooth.