Modeling Cognitive Trends in Preclinical Alzheimer’s Disease (AD) via Distributions over Permutations
- 8.8k Downloads
This paper presents an algorithm to identify subsets of subjects who share similarities in the context of imaging and clinical measurements within a cohort of cognitively healthy individuals at risk for Alzheimer’s disease (AD). In particular, we wish to evaluate how patterns in the subjects’ cognitive scores or PIB-PET image measurements are associated with a clinical assessment of risk of developing AD, image based measures, and future cognitive decline. The challenge here is that all the participants are asymptomatic, our predictors are noisy and heterogeneous, and the disease specific signal, when present, is weak. As a result, off-the-shelf methods do not work well. We develop a model that uses a probability distribution over the set of permutations to represent the data; this yields a distance measure robust to these issues. We then show that our algorithm produces consistent and meaningful groupings of subjects based on their cognitive scores and that it provides a novel and interesting representation of measurements from PIB-PET images.
- 7.Kondor, R.: Group theoretical methods in machine learning. Ph.D. thesis, Columbia University (2008)Google Scholar
- 8.Kondor, R., Howard, A., Jebara, T.: Multi-object tracking with representations of the symmetric group. In: AISTATS (2007)Google Scholar
- 9.Ng, A.Y., Jordan, M.I., Weiss, Y.: On spectral clustering: analysis and an algorithm. In: NIPS, pp. 849–856 (2002)Google Scholar
- 11.Sperling, R.A., Aisen, P.S., Beckett, L.A., et al.: Toward defining the preclinical stages of Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement. 7(3), 280–292 (2011)CrossRefGoogle Scholar
- 12.Young, A.L., Oxtoby, N.P., Huang, J., et al.: Multiple orderings of events in disease progression. Inf. Process. Med. Imaging 24, 711–722 (2015)Google Scholar