Congratulations to Akshay Ashok and Grace Cheng on being selected to the UF Center for Undergraduate Research AI Scholars Program.
This scholarship is part of the University Scholars Program and was established to introduce outstanding full-time undergraduate students to the exciting world of academic research. In this program, students work one-on-one with UF faculty on selected research projects. Both are mentored by Dr. Ruogu Fang.
Title: Diffusion Model Synthesis: Evaluating Older Aging vs. Parkinson’s Disease Specific Biomarkers in UK Biobank Fundus Imaging.
This project expands upon a previous study in which researchers applied deep learning and traditional machine learning models to a dataset of fundus images. In that study, deep learning models outperformed traditional ML models in predicting Parkinson’s in patients. In our project, we aim to validate this performance of deep learning models in predicting PD. We will accomplish this by using a diffusion model to synthesize artificial fundus images from the original image dataset, effectively augmenting the overall dataset for elderly patients and patients with PD. By comparing settings with the original and augmented datasets, we hope to find whether diffusion model synthesis allows deep learning models to use the correct biomarkers to predict Parkinson’s disease from fundus images.
Title: Aging in Caenorhabditis Elegans
This project aims to use a machine learning model to predict the age and lifespan of C. elegans worms from video footage. C. elegans worms are a useful model for human aging because they have similar physiological changes in their cellular systems at multiple levels compared to humans, paralleling lifespan stages. Through analysis of video footage, the model will aim to combine physiological features with movement patterns to predict stages of life, age, and prediction of death for C. elegans.