Detalhe da pesquisa
1.
Aberrant functional network connectivity in psychopathy from a large (N = 985) forensic sample.
Hum Brain Mapp
; 39(6): 2624-2634, 2018 06.
Artigo
em Inglês
| MEDLINE | ID: mdl-29498761
2.
Replicability of time-varying connectivity patterns in large resting state fMRI samples.
Neuroimage
; 163: 160-176, 2017 12.
Artigo
em Inglês
| MEDLINE | ID: mdl-28916181
3.
Cross-Frequency rs-fMRI Network Connectivity Patterns Manifest Differently for Schizophrenia Patients and Healthy Controls.
IEEE Signal Process Lett
; 23(8): 1076-1080, 2016 Aug.
Artigo
em Inglês
| MEDLINE | ID: mdl-28018124
4.
Potential Therapeutic Benefits of Babywearing.
Creat Nurs
; 22(1): 17-23, 2016 Feb 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-30188302
5.
Mutually temporally independent connectivity patterns: a new framework to study the dynamics of brain connectivity at rest with application to explain group difference based on gender.
Neuroimage
; 107: 85-94, 2015 Feb 15.
Artigo
em Inglês
| MEDLINE | ID: mdl-25485713
6.
Dynamic coherence analysis of resting fMRI data to jointly capture state-based phase, frequency, and time-domain information.
Neuroimage
; 120: 133-42, 2015 Oct 15.
Artigo
em Inglês
| MEDLINE | ID: mdl-26162552
7.
Assessing dynamic brain graphs of time-varying connectivity in fMRI data: application to healthy controls and patients with schizophrenia.
Neuroimage
; 107: 345-355, 2015 Feb 15.
Artigo
em Inglês
| MEDLINE | ID: mdl-25514514
8.
Explainable fuzzy clustering framework reveals divergent default mode network connectivity dynamics in schizophrenia.
Front Psychiatry
; 15: 1165424, 2024.
Artigo
em Inglês
| MEDLINE | ID: mdl-38495909
9.
Identifying EEG Biomarkers of Depression with Novel Explainable Deep Learning Architectures.
bioRxiv
; 2024 Mar 21.
Artigo
em Inglês
| MEDLINE | ID: mdl-38562835
10.
Identifying Reproducibly Important EEG Markers of Schizophrenia with an Explainable Multi-Model Deep Learning Approach.
bioRxiv
; 2024 Feb 13.
Artigo
em Inglês
| MEDLINE | ID: mdl-38405889
11.
Uncovering Effects of Schizophrenia upon a Maximally Significant, Minimally Complex Subset of Default Mode Network Connectivity Features.
bioRxiv
; 2024 Apr 25.
Artigo
em Inglês
| MEDLINE | ID: mdl-38712056
12.
Explainable Fuzzy Clustering Framework Reveals Divergent Default Mode Network Connectivity Dynamics in Schizophrenia.
bioRxiv
; 2023 Feb 14.
Artigo
em Inglês
| MEDLINE | ID: mdl-36824777
13.
A Novel Explainable Fuzzy Clustering Approach for fMRI Dynamic Functional Network Connectivity Analysis.
bioRxiv
; 2023 Jan 31.
Artigo
em Inglês
| MEDLINE | ID: mdl-36778353
14.
Towards greater neuroimaging classification transparency via the integration of explainability methods and confidence estimation approaches.
Inform Med Unlocked
; 372023.
Artigo
em Inglês
| MEDLINE | ID: mdl-37035832
15.
Neuropsychiatric Disorder Subtyping Via Clustered Deep Learning Classifier Explanations.
Annu Int Conf IEEE Eng Med Biol Soc
; 2023: 1-4, 2023 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-38083012
16.
Hyperlocal Spatial Flows in BOLD fMRI Expose Novel Brain-Based Correlates of Schizophrenia.
Annu Int Conf IEEE Eng Med Biol Soc
; 2023: 1-4, 2023 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-38083298
17.
A Novel Explainable Fuzzy Clustering Approach for fMRI Dynamic Functional Network Connectivity Analysis.
Annu Int Conf IEEE Eng Med Biol Soc
; 2023: 1-4, 2023 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-38083353
18.
A Convolutional Autoencoder-based Explainable Clustering Approach for Resting-State EEG Analysis.
Annu Int Conf IEEE Eng Med Biol Soc
; 2023: 1-4, 2023 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-38083554
19.
CROSS-SAMPLING RATE TRANSFER LEARNING FOR ENHANCED RAW EEG DEEP LEARNING CLASSIFIER PERFORMANCE IN MAJOR DEPRESSIVE DISORDER DIAGNOSIS.
bioRxiv
; 2023 Nov 16.
Artigo
em Inglês
| MEDLINE | ID: mdl-38014293
20.
Evaluating Augmentation Approaches for Deep Learning-based Major Depressive Disorder Diagnosis with Raw Electroencephalogram Data.
bioRxiv
; 2023 Dec 18.
Artigo
em Inglês
| MEDLINE | ID: mdl-38187601