Our mission is to create methods to fit the science and not make science fit the methods.
Specifically, we are interested in the following questions that have clinical relevance:
We are also interested in the following frameworks that have computational relevance:
We form small teams comprising individuals with complementary expertise and work persistently to build comprehensive solutions. If you are interested in joining us, then we encourage you to contact an active lab member and talk about your interests.
We are grateful for funding from the American Heart Association, the National Institute on Aging, the National Heart, Lung, and Blood Institute, the National Cancer Institute, the Artificial Intelligence and Technology Collaboratories (AITC) for Aging Research program, and the National Institute of Diabetes and Digestive and Kidney Diseases. We also thank the Karen Toffler Charitable Trust, Johnson & Johnson Enterprise Innovation Inc., and Visterra Inc., for funding our work.
– Machine learning (MS650)
New paper! Fusion of low-level voice descriptors for dementia, published in the Journal of Alzheimer's Disease.October 2023
New paper! Large language models in neurology, published in Neurology.September 2023
New grant! We received an Ignition Award from Boston University to create an AI-based tool for dementia assessment.September 2023
New paper! Deep learning to predict progression risk on cognitively impaired individuals, published in iScience.May 2023
New paper! Machine learning in clinical trials: Applications to neurology, published in Neurotherapeutics.April 2023
Tejus Surendran transitions from a staff scientist in our lab to a PhD student at Carnegie Mellon University.March 2023
Matthew Miller got matched to MGH Radiology.March 2023
Akshara Balachandra got matched to Stanford Neurology.March 2023
Joyce Lee got matched to BMC Neurology.