Age Related
Age-related research focuses on understanding and predicting the biological processes of aging, aiming to identify biomarkers and develop interventions to improve healthspan and lifespan. Current research utilizes machine learning, particularly deep learning models like 3D CNNs and ResNets, along with techniques like federated learning and contrastive learning, to analyze diverse data sources including MRI scans, metabolomics data, fluorescence spectroscopy, and voice recordings. These efforts are significant for improving diagnostic accuracy of age-related diseases like Alzheimer's, personalizing healthcare interventions, and developing more effective tools for monitoring aging trajectories.
Papers
Deep Learning Domain Adaptation to Understand Physico-Chemical Processes from Fluorescence Spectroscopy Small Datasets: Application to Ageing of Olive Oil
Umberto Michelucci, Francesca Venturini
Positive-Unlabelled Learning for Identifying New Candidate Dietary Restriction-related Genes among Ageing-related Genes
Jorge Paz-Ruza, Alex A. Freitas, Amparo Alonso-Betanzos, Bertha Guijarro-Berdiñas