Ariana E. Anderson

Affiliations:
  • University of California, Los Angeles, Department of Psychiatry and Biobehavioral Sciences, USA


According to our database1, Ariana E. Anderson authored at least 14 papers between 2010 and 2019.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2019
Feature Fallacy: Complications with Interpreting Linear Decoding Weights in fMRI.
Proceedings of the Explainable AI: Interpreting, 2019

2016
Electronic health record phenotyping improves detection and screening of type 2 diabetes in the general United States population: A cross-sectional, unselected, retrospective study.
J. Biomed. Informatics, 2016

Decoding the Encoding of Functional Brain Networks: an fMRI Classification Comparison of Non-negative Matrix Factorization (NMF), Independent Component Analysis (ICA), and Sparse Coding Algorithms.
CoRR, 2016

2014
The utility of data-driven feature selection: Re: Chu et al. 2012.
NeuroImage, 2014

Non-negative matrix factorization of multimodal MRI, fMRI and phenotypic data reveals differential changes in default mode subnetworks in ADHD.
NeuroImage, 2014

Cognitive and neurodevelopmental benefits of extended formula-feeding in infants: Re: Deoni et al 2013.
NeuroImage, 2014

Multimodal diagnosis of epilepsy using conditional dependence and multiple imputation.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2014

2013
Balancing Clinical and Pathologic Relevance in the Machine Learning Diagnosis of Epilepsy.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013

Reducing Clinical Trial Costs by Detecting and Measuring the Placebo Effect and Treatment Effect Using Brain Imaging.
Proceedings of the Medicine Meets Virtual Reality 20 - NextMed, 2013

2012
Parameter Selection in Mutual Information-Based Feature Selection in Automated Diagnosis of Multiple Epilepsies Using Scalp EEG.
Proceedings of the Second International Workshop on Pattern Recognition in NeuroImaging, 2012

2011
Common component classification: What can we learn from machine learning?
NeuroImage, 2011

Large sample group independent component analysis of functional magnetic resonance imaging using anatomical atlas-based reduction and bootstrapped clustering.
Int. J. Imaging Syst. Technol., 2011

Real-Time Functional MRI Classification of Brain States Using Markov-SVM Hybrid Models: Peering Inside the rt-fMRI Black Box.
Proceedings of the Machine Learning and Interpretation in Neuroimaging, 2011

2010
Classification of spatially unaligned fMRI scans.
NeuroImage, 2010


  Loading...