Optimized Naive-Bayes and Decision Tree Approaches for fMRI Smoking Cessation Classification
This paper aims at developing new theory-driven biomarkers by implementing and evaluating novel techniques from resting-state scans that can be used in relapse prediction for nicotine-dependent patients and future treatment efficacy. Two classes of patients were studied. One class took the drug N-ac...
Saved in:
Main Authors: | Amirhessam Tahmassebi, Amir H. Gandomi, Mieke H. J. Schulte, Anna E. Goudriaan, Simon Y. Foo, Anke Meyer-Baese |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2018-01-01
|
Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2018/2740817 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Controllability of Functional and Structural Brain Networks
by: Ali Moradi Amani, et al.
Published: (2024-01-01) -
The Benefits of Smoking Cessation
by: Nick R Anthonisen
Published: (2003-01-01) -
Smoking cessation in primary care
by: Yi Hui Adela Lua, et al.
Published: (2024-01-01) -
Altered Brain Activation in Early Drug-Naive Parkinson’s Disease during Heat Pain Stimuli: An fMRI Study
by: Ying Tan, et al.
Published: (2015-01-01) -
BOLD Noise Assumptions in fMRI
by: Alle Meije Wink, et al.
Published: (2006-01-01)