Relating biological and clinical features of Alzheimers patients with predictive clustering trees
published: Oct. 21, 2015, recorded: October 2015, views: 40
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
This paper presents experiments with Predictive Clustering Trees that uncover several subpopulations of the Alzheimer’s disease patients. Our experiments are based on previous research that identified the everyday cognition as one of the most important testing domains in the clinical diagnostic process for the Alzheimer’s disease. We are investigating which biological features have a role in the progression of the disease by observing behavioral response of the patients and their study partners. Our dataset includes 342 male and 317 female patients from the ADNI database that are described with 243 clinical and biological attributes. The resulting clusters, described in terms of biological features, show behavioral and gender specific differences between clusters of patients with progressed disease. These findings suggest a possibility that the Alzheimer’s disease is manifested through different biological pathways.
Download slides: sikdd2015_breskvar_alzheimer_patients_01.pdf (831.7 KB)
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !