D Rangaprakash
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Explore the profile of D Rangaprakash including associated specialties, affiliations and a list of published articles.
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39
Citations
504
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Recent Articles
11.
Gururaja C, Rangaprakash D, Deshpande G
Int J Public Ment Health Neurosci
. 2021 Sep;
7(1):8-13.
PMID: 34553079
Yoga is an integrative mind-body system of wellbeing developed in India since at least three millennia. Yoga has gained considerable attention in recent decades, partly driven by recent research and...
12.
Wong W, Rangaprakash D, Larson M, Diaz-Fong J, Tadayonnejad R, Leuchter A, et al.
Brain Stimul
. 2021 Aug;
14(5):1197-1200.
PMID: 34339891
No abstract available.
13.
Rowe O, Rangaprakash D, Weerasekera A, Godbole N, Haxton E, James P, et al.
Mol Genet Metab
. 2021 Jul;
133(4):386-396.
PMID: 34226107
Objective: Our study aimed to quantify structural changes in relation to metabolic abnormalities in the cerebellum, thalamus, and parietal cortex of patients with late-onset GM2-gangliosidosis (LOGG), which encompasses late-onset Tay-Sachs...
14.
Ingalhalikar M, Shinde S, Karmarkar A, Rajan A, Rangaprakash D, Deshpande G
IEEE Trans Biomed Eng
. 2021 May;
68(12):3628-3637.
PMID: 33989150
Objective: The larger sample sizes available from multi-site publicly available neuroimaging data repositories makes machine-learning based diagnostic classification of mental disorders more feasible by alleviating the curse of dimensionality. However,...
15.
Barry R, Babu S, Anteraper S, Triantafyllou C, Keil B, Rowe O, et al.
Neuroimage Clin
. 2021 Apr;
30:102648.
PMID: 33872993
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease of the central nervous system that results in a progressive loss of motor function and ultimately death. It is critical, yet also...
16.
Rangaprakash D, Odemuyiwa T, Narayana Dutt D, Deshpande G
Brain Inform
. 2020 Nov;
7(1):19.
PMID: 33242116
Various machine-learning classification techniques have been employed previously to classify brain states in healthy and disease populations using functional magnetic resonance imaging (fMRI). These methods generally use supervised classifiers that...
17.
Rangaprakash D, Tadayonnejad R, Deshpande G, ONeill J, Feusner J
Brain Imaging Behav
. 2020 Aug;
15(3):1622-1640.
PMID: 32761566
The hemodynamic response function (HRF) represents the transfer function linking neural activity with the functional MRI (fMRI) signal, modeling neurovascular coupling. Since HRF is influenced by non-neural factors, to date...
18.
Lanka P, Rangaprakash D, Gotoor S, Dretsch M, Katz J, Denney Jr T, et al.
Data Brief
. 2020 Feb;
29:105213.
PMID: 32090157
Resting-state functional Magnetic Resonance Imaging (rs-fMRI) has been extensively used for diagnostic classification because it does not require task compliance and is easier to pool data from multiple imaging sites,...
19.
Zhao S, Rangaprakash D, Liang P, Deshpande G
Brain Inform
. 2019 Dec;
6(1):8.
PMID: 31792630
Objective: It is important to identify brain-based biomarkers that progressively deteriorate from healthy to mild cognitive impairment (MCI) to Alzheimer's disease (AD). Cortical thickness, amyloid-ß deposition, and graph measures derived...
20.
Lanka P, Rangaprakash D, Dretsch M, Katz J, Denney Jr T, Deshpande G
Brain Imaging Behav
. 2019 Nov;
14(6):2378-2416.
PMID: 31691160
There are growing concerns about the generalizability of machine learning classifiers in neuroimaging. In order to evaluate this aspect across relatively large heterogeneous populations, we investigated four disorders: Autism spectrum...