Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Jagath C Rajapakse

7PUBLICATIONS
3CO-AUTHORS
CognitionNeural networksMolecular targetsDeep learningPredictive and prognostic markers
Featured researcher

Get your video featured.

JoVEPublish with JoVE
Featured researcher

Get your video featured.

JoVEPublish with JoVE
Journal

Publications (7)

Sort by Publication Date:
|Aug 13, 2025
Disentangling shared and unique brain functional changes associated with clinical severity and cognitive phenotypes in schizophrenia via deep learning.

Jing Xia, Yi Hao Chan, Deepank Girish

|Apr 18, 2024
Sparse Deep Neural Network for Encoding and Decoding the Structural Connectome.

Satya P Singh, Sukrit Gupta, Jagath C Rajapakse

|Nov 28, 2022
Deep learning and multi-omics approach to predict drug responses in cancer.

Conghao Wang, Xintong Lye, Rama Kaalia

|Feb 28, 2022
Decoding task specific and task general functional architectures of the brain.

Sukrit Gupta, Marcus Lim, Jagath C Rajapakse

|May 07, 2020
Iterative consensus spectral clustering improves detection of subject and group level brain functional modules.

Sukrit Gupta, Jagath C Rajapakse

|Dec 21, 2019
A deep neural network approach to predicting clinical outcomes of neuroblastoma patients.

Léon-Charles Tranchevent, Francisco Azuaje, Jagath C Rajapakse

Pageof 2

Frequent Collaborators

3 joint publications

Sukrit Gupta

1 joint publications

Satya P Singh

1 joint publications

Kang Sim

Frequent Collaborators

3 joint publications

Sukrit Gupta

1 joint publications

Satya P Singh

1 joint publications

Kang Sim

Top Related Videos

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on : Jun 26, 2013

15.8K
DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data
09:47

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data

Published on : Dec 15, 2023

1.0K
See more related videos

Top Related Videos

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on : Jun 26, 2013

15.8K
DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data
09:47

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data

Published on : Dec 15, 2023

1.0K
See more related videos