Maria Pierce, Louise Foley, Bridget Kiely, Aisling Croke, James Larkin, Susan M Smith, Barbara Clyne, Edel Murphy
Embedding formal and experiential public and patient involvement training in a structured PhD programme: process and impact evaluation
Research involvement and engagement
capillary ultrastructure human skeletal muscles dynamic prone alterations response many stimuli eg systemic pathologies diabetes mellitus arterial hypertension using transmission electron microscopy tem images several studies conducted quantify capillary ultrastructure means morphometry deep learning techniques like convolutional neural networks cnns utilized extract datadriven characteristics recognize patterns hence aim study train cnn identify morphometric patterns differ capillaries muscle biopsies healthy participants patients systemic pathologies purpose hypothesis generation retrospective study used 1810 electron micrographs human skeletal muscle capillaries derived 70 study participants classified healthy controls patients dependence absence presence documented history diabetes mellitus arterial hypertension peripheral arterial disease using micrographs pretrained openaccess cnn resnet101 trained discriminate micrographs capillaries two groups cnn highest diagnostic accuracies training subsequently compared manual quantitative analysis capillary ultrastructure distinguish healthy controls patients using classification controls patients allocation reference receiveroperatingcharacteristics rocanalysis manually obtained bm thickness showed best diagnostic accuracy morphometric indicators area roccurve auc 0657 0050 best performing cnn demonstrated diagnostic accuracy 79 sensitivity 93 specificity 92 delongtest roccurves showed significant difference p 0001 auc best performing cnn bm thickness underlying morphology responsible network prediction focuses mainly debridement pericytes hypothesisgenerating approach using pretrained cnn distinguishes capillaries depicted electron micrographs healthy controls participants systemic pathology accurately commonly used morphometric analysis