Author

Humberto González

ORCID 0000-0002-9883-2053Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:machine learning (classical)· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Assay:imaging· 1

Frequent Co-Authors

Matthew KolladaiD· 2 shared Monika S. MellemiD· 2 shared Parvez AhammadiD· 2 shared William J. MartiniD· 2 shared Yuelu Liu· 2 shared Annette Madrid· 1 shared Atul R. Mahableshwarkar· 1 shared

Activity by Year

2018-2019 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 21 mutual co-author links

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2 shared papersNeuroscience

Matthew KolladaORCID

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2 papers

Recent·Most cited

NeuroscienceBiological Psychiatry Cognitive Neuroscience and NeuroimagingPeer-reviewedJul 30, 2019

Machine learning models identify multimodal measurements highly predictive of transdiagnostic symptom severity for mood, anhedonia, and anxiety

Monika S. Mellem, Yuelu Liu, Humberto González…·Parvez Ahammad

The paper develops machine learning models using multimodal data to predict transdiagnostic psychiatric symptom severity, achieving high variance explanation and revealing key predictors.

40 citations

humanbulk RNA-seq

𝕏 PostBluesky

NeurosciencebioRxivPreprintDec 18, 2018

Highly Predictive Transdiagnostic Features Shared across Schizophrenia, Bipolar Disorder, and ADHD Identified Using a Machine Learning Based Approach

Yuelu Liu, Monika S. Mellem, Humberto González…·Parvez Ahammad

The paper identifies transdiagnostic features shared across schizophrenia, bipolar disorder, and ADHD using machine learning on self-reported data, showing high predictive power for distinguishing patients from controls.

3 citations

humanmachine learning (classical)

𝕏 PostBluesky