Author

Jonathan D. Mahnken

University of Kansas Medical Center

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Neuroscience· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 1 Organism:human· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Alzheimer’s Disease Neuroimaging Initiative· 1 shared Chong WuiD· 1 shared Ivo D. DinoviD· 1 shared Jian KangiD· 1 shared Jinxiang HuiD· 1 shared Prabhakar ChaliseiD· 1 shared Yanming LiiD· 1 shared

Activity by Year

2021-2021 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 21 mutual co-author links

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1 shared paperNeuroscience

Alzheimer’s Disease Neuroimaging Initiative

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1 paper

Recent·Most cited

A machine-learning approach for detection of local brain networks and marginally weak signals identifies novel AD/MCI differentiating connectomic neuroimaging biomarkers

Yanming Li, Jian Kang, Chong Wu, Ivo D. Dinov, Jinxiang Hu, Prabhakar Chalise, Jonathan D. Mahnken, Alzheimer’s Disease Neuroimaging Initiative

The paper introduces a machine learning method to detect brain connectomic biomarkers differentiating Alzheimer's disease and mild cognitive impairment using FDG-PET data.

bioRxiv · Jul 29, 2021 · PreprintNeuroscience