2021-2022 PRojects


Project Title: Forecasting Alzheimer’s Disease

Professor: Madalina Fiterau

Lab/Research Group: Information Fusion Lab

The Information Fusion Lab at UMass Amherst CICS focuses on ML for multimodal data, including methods that support a wide range of biomedical applications. Our research includes a wide variety of topics including deep learning for the fusion of multi-resolution time series, images and structured information, the incorporation of domain knowledge or saliency in imaging and integration of multiple views for MRI analysis. Most recently, we introduced new methods for normalizing flows and transfer of causal models. Please see our research page for a full list of projects and our GitHub page for code releases.


Lab home page: https://groups.cs.umass.edu/infofusion/home/



Project 4Thought aims to preemptively forecast Alzheimer’s disease. We are looking to identify subjects who will get Alzheimer’s at least 2 years ahead of the standard diagnosis, based on brain structural MRIs and cognitive test scores. We introduce forecasting models that leverage multimodal data and domain knowledge.

4Thought was homegrown here at CICS in the Information Fusion Lab, supported by the Manning/IALS Innovation Award. 4Thought was initially led by Joie Wu, and is now led by Sidong Zhang. Our mentors from IALS are Peter Reinhart and Karen Utgoff.

The prerequisites are:

  • intermediate programing skills

  • logical reasoning ability

  • mathematics skills (basic linear algebra, calculus, statistics and probability)

Here are some examples of skills you will gain:

  • how to design and implement models for medical image segmentation and disease diagnosis/prediction

  • how to appropriately evaluate machine learning models (how to design experiments, select test sets, perform cross-validation)

  • how to optimize models, how to efficiently train and test them

Project page: https://groups.cs.umass.edu/infofusion/4thought-early-forecasting-of-alzheimers-disease/