Author

Manpreet Kaur Singh

Stanford MedicineORCID 0000-0002-4373-3293Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Organism:human· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Aaron J. GorelikiD· 1 shared Akua F. NimarkoiD· 1 shared Ananya Nrusimha· 1 shared Anthony Joseph GifuniiD· 1 shared Artenisa Kulla· 1 shared Giana Isabella TeresiiD· 1 shared Ian H. GotlibiD· 1 shared Jaclyn Schwartz KirshenbaumiD· 1 shared

Activity by Year

2020-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperNeuroscience

Aaron J. GorelikORCID

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2 papers

Recent·Most cited

Default Mode and Salience Network Alterations in Suicidal and Non-Suicidal Self-Injurious Thoughts and Behaviors in Adolescents with Depression

Tiffany Cheing Ho, Johanna C. Walker, Giana Isabella Teresi, Artenisa Kulla, Jaclyn Schwartz Kirshenbaum, Anthony Joseph Gifuni, Manpreet Kaur Singh, Ian H. Gotlib

The paper examines brain network coherence differences between adolescents with depression and suicidal or non-suicidal self-injurious thoughts, identifying specific neural patterns associated with these behaviors.

Translational Psychiatry · Jan 12, 2021Peer-reviewedNeuroscience

Applying Machine Learning to Increase Efficiency and Accuracy of Meta-Analytic Review

Aaron J. Gorelik, Mark G. Gorelik, Kathryn K. Ridout, Akua F. Nimarko, Virginia D. Peisch, Shamanth R. Kuramkote, Michelle Low, Tracy Pan, Simirthi Singh, Ananya Nrusimha, Manpreet Kaur Singh

This paper develops a machine learning approach to automate paper selection for meta-analyses, showing it reduces review time while maintaining accuracy comparable to human reviewers.

bioRxiv · Oct 6, 2020 · PreprintNeuroscience