Author

Karteek Popuri

Memorial University of NewfoundlandORCID 0000-0002-1729-3255Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Bioinformatics· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:benchmarking· 2 Organism:human· 2 Assay:imaging· 2 Approach:statistical model· 2 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

Ashley A. HeywoodiD· 2 shared Jane K. StocksiD· 2 shared Lei WangiD· 2 shared Mirza Faisal BegiD· 2 shared Aggelos K. KatsaggelosiD· 1 shared Alexei TayloriD· 1 shared Fengqing ZhangiD· 1 shared Gangyi FengiD· 1 shared

Activity by Year

2021-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersNeuroscience

Ashley A. HeywoodORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Investigating the temporal pattern of neuroimaging-based brain age estimation as a biomarker for Alzheimer's Disease related neurodegeneration

Alexei Taylor, Fengqing Zhang, Xin Niu, Ashley A. Heywood, Jane K. Stocks, Gangyi Feng, Karteek Popuri, Mirza Faisal Beg, Lei Wang, the Alzheimer’s Disease Neuroimaging Initiative

This study examines the temporal pattern of brain age gaps in Alzheimer's Disease progression using longitudinal neuroimaging data and finds a faster increase in BAG for those progressing from MCI to AD.

NeuroImage · Sep 9, 2022Peer-reviewedNeuroscience

Transfer Learning for Predicting Conversion from Mild Cognitive Impairment to Dementia of Alzheimer Type based on 3D-Convolutional Neural Network

Jinhyeong Bae, Jane K. Stocks, Ashley A. Heywood, Youngmoon Jung, Lisanne Michelle Jenkins, Virginia B. Hill, Aggelos K. Katsaggelos, Karteek Popuri, Howie J. Rosen, Mirza Faisal Beg, Lei Wang

This paper develops a 3D-CNN model using transfer learning to predict conversion from MCI to DAT, achieving 82.4% accuracy and identifying key brain regions associated with disease progression.

Neurobiology of Aging · Mar 1, 2021Peer-reviewedBioinformatics