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D. Rangaprakash
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2020 – today
- 2023
- [c5]Laura A. Chicos
, D. Rangaprakash, Robert L. Barry, Hugh M. Herr:
Resting State Neurophysiology of Agonist Antagonist Myoneural Interface in Transtibial Amputees. NER 2023: 1-5 - 2021
- [j11]Madhura Ingalhalikar
, Sumeet Shinde
, Arnav Karmarkar
, Archith Rajan, D. Rangaprakash, Gopikrishna Deshpande
:
Functional Connectivity-Based Prediction of Autism on Site Harmonized ABIDE Dataset. IEEE Trans. Biomed. Eng. 68(12): 3628-3637 (2021) - [c4]Da Yan, Shengbin Wu, Mirza Tanzim Sami, Abdullateef Ibrahim Almudaifer, Zhe Jiang
, Haiquan Chen, D. Rangaprakash, Gopikrishna Deshpande
, Yueen Ma:
Improving Brain Dysfunction Prediction by GAN: A Functional-Connectivity Generator Approach. IEEE BigData 2021: 1514-1522 - [c3]Yueen Ma, Da Yan, Cheng Long, D. Rangaprakash, Gopikrishna Deshpande
:
Predicting Autism Spectrum Disorder from Brain Imaging Data by Graph Convolutional Network. IJCNN 2021: 1-8 - 2020
- [j10]D. Rangaprakash, Toluwanimi Odemuyiwa, D. Narayana Dutt, Gopikrishna Deshpande
:
Density-based clustering of static and dynamic functional MRI connectivity features obtained from subjects with cognitive impairment. Brain Informatics 7(1): 19 (2020) - [j9]Mohammed A. Syed
, Zhi Yang
, D. Rangaprakash, Xiaoping Hu
, Michael N. Dretsch, Jeffrey S. Katz, Thomas S. Denney, Gopikrishna Deshpande
:
DisConICA: a Software Package for Assessing Reproducibility of Brain Networks and their Discriminability across Disorders. Neuroinformatics 18(1): 87-107 (2020)
2010 – 2019
- 2019
- [j8]Sinan Zhao, D. Rangaprakash
, Peipeng Liang, Gopikrishna Deshpande
:
Deterioration from healthy to mild cognitive impairment and Alzheimer's disease mirrored in corresponding loss of centrality in directed brain networks. Brain Informatics 6(1): 8 (2019) - 2018
- [j7]Xinyu Zhao, D. Rangaprakash, Bowen Yuan, Thomas S. Denney Jr., Jeffrey S. Katz, Michael N. Dretsch, Gopikrishna Deshpande
:
Investigating the Correspondence of Clinical Diagnostic Grouping With Underlying Neurobiological and Phenotypic Clusters Using Unsupervised Machine Learning. Frontiers Appl. Math. Stat. 4: 25 (2018) - 2017
- [j6]D. Rangaprakash
:
Binarized Brain Connectivity: A Novel Autocorrelation-Based Iterative Synchronization Technique. IEEE Trans. Signal Inf. Process. over Networks 3(4): 660-668 (2017) - 2015
- [j5]D. Rangaprakash
, D. Narayana Dutt:
Study of wrist pulse signals using time domain spatial features. Comput. Electr. Eng. 45: 100-107 (2015) - [j4]Gopikrishna Deshpande
, Peng Wang, D. Rangaprakash
, Bogdan M. Wilamowski:
Fully Connected Cascade Artificial Neural Network Architecture for Attention Deficit Hyperactivity Disorder Classification From Functional Magnetic Resonance Imaging Data. IEEE Trans. Cybern. 45(12): 2668-2679 (2015) - [c2]Vajarala Ashikh, Gopikrishna Deshpande
, D. Rangaprakash
, D. Narayana Dutt:
Clustering of dynamic functional connectivity features obtained from functional Magnetic Resonance Imaging data. ICACCI 2015: 308-312 - 2014
- [j3]D. Rangaprakash
, N. Pradhan:
Study of phase synchronization in multichannel seizure EEG using nonlinear recurrence measure. Biomed. Signal Process. Control. 11: 114-122 (2014) - [j2]D. Rangaprakash
:
Connectivity analysis of multichannel EEG signals using recurrence based phase synchronization technique. Comput. Biol. Medicine 46: 11-21 (2014) - [c1]D. Rangaprakash
, D. Narayana Dutt:
Study of wrist pulse signals using a bi-modal Gaussian model. ICACCI 2014: 2422-2425 - 2013
- [j1]D. Rangaprakash
, Xiaoping Hu
, Gopikrishna Deshpande
:
Phase Synchronization in Brain Networks derived from Correlation between Probabilities of Recurrences in Functional MRI Data. Int. J. Neural Syst. 23(2) (2013)
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