Journal article
The Use of Random Forests to Classify Amyloid Brain PET.
Abstract
PURPOSE: To evaluate random forests (RFs) as a supervised machine learning algorithm to classify amyloid brain PET as positive or negative for amyloid deposition and identify key regions of interest for stratification.
METHODS: The data set included 57 baseline F-florbetapir (Amyvid; Lilly, Indianapolis, IN) brain PET scans in participants with severe white matter disease, presenting with either transient ischemic attack/lacunar stroke or mild …
Authors
Zukotynski K; Gaudet V; Kuo PH; Adamo S; Goubran M; Scott C; Bocti C; Borrie M; Chertkow H; Frayne R
Journal
Clinical Nuclear Medicine, Vol. 44, No. 10, pp. 784–788
Publisher
Wolters Kluwer
Publication Date
October 2019
DOI
10.1097/rlu.0000000000002747
ISSN
0363-9762