Thesis title: Developing a universal machine learning model to detect cellular senescence in a variety of cells types
Supervisors: Arnold Lining Ju, Hala Zreiqat, Zufu Lu
Thesis abstract:
«p»The significance of endothelial cell senescence extends beyond the endothelium itself and can impact the functions and phenotypes of the surrounding cells, including immune cells and smooth muscle cells through the paracrine signalling and senescence-associated secretory phenotype (SASP) factors. It is important that we are able to identify and understand how these different cells interact together and what influences endothelial cell senescence. Incorporating the use of and developing accurate AI machine learning models can lead us to extracting crucial information towards identifying the biomarkers that are predictive of endothelial cell senescence.«/p»