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Non-Binary Approaches for Classification of Amyloid Brain PET

Abstract

Machine learning (ML) is increasingly used in medical imaging. This paper provides pilot data of decision trees and random forests (RFs) to predict if a 18F-florbetapir brain positron emission tomography (PET) is positive or negative for amyloid deposition based on quantitative data analysis. The dataset included 55 18F-florbetapir brain PETs in participants with severe white matter disease and mild cognitive impairment (MCI), early Alzheimer's …

Authors

Zukotvnski K; Gaudet VC; Kuo P; Adamo S; Goubran M; Bocti C; Borrie M; Chertkow H; Frayne R; Hsiung R

Volume

00

Pagination

pp. 206-211

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Publication Date

May 21, 2019

DOI

10.1109/ismvl.2019.00043

Name of conference

2019 IEEE 49th International Symposium on Multiple-Valued Logic (ISMVL)