Lab Affiliation: Craig Stark Lab
Title: Improving clinical efficiency in Alzheimer’s disease screening and progression tracking using statistical machine learning
Abstract: Alzheimer’s is a costly disease that affects millions of people. Its prevalence is exacerbated by a severe shortage of clinical experts. Considering these trends, improving clinical efficiency by empowering primary care providers to screen for Alzheimer’s disease (AD) is a paramount goal. While past work on AD diagnosis has demonstrated the utility of machine learning tools using multimodal biomarkers, few studies have focused on cost-effective data for AD prediction. In my talk, I will discuss several projects that address these gaps in the field. This presentation is a practice talk for my upcoming Advancement to Candidacy Exam and open to graduate students for peer feedback.