Multimodal machine learning study of neurodegenerative diseases
Neurodegenerative disease is a leading cause of death in the world. However, limited treatment options are currently available. The changes of preclinical symptoms could happen years if not decades earlier before the threshold of clinical diagnosis is met. It is therefore important to identify people of high risk as early as possible. Recent machine learning models are able to combine different data types for accurate prediction. The objective of this study is to leverage the huge amount of data collected from UK Biobank and other large cohorts, and build machine learning methods to predict disease risk and subtypes. Our study would have the potential to identify people of high disease risk at an early stage, which would help future clinical intervention and risk mitigation. The study is anticipated to last for five years.