Author

Michael Alexander Riegler

University of OsloORCID 0000-0002-3153-2064Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Organism:human· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Enrique Garcia-CejaiD· 1 shared Jim TørreseniD· 1 shared Ketil Joachim OedegaardiD· 1 shared Lena Antonsen StabelliD· 1 shared Ole Bernt FasmeriD· 1 shared Petter JakobseniD· 1 shared Tine NordgreeniD· 1 shared

Activity by Year

2020-2020 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 21 mutual co-author links

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1 shared paperBioinformatics

Enrique Garcia-CejaORCID

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1 paper

Recent·Most cited

Applying machine learning in motor activity time series of depressed bipolar and unipolar patients.

Petter Jakobsen, Enrique Garcia-Ceja, Michael Alexander Riegler, Lena Antonsen Stabell, Tine Nordgreen, Jim Tørresen, Ole Bernt Fasmer, Ketil Joachim Oedegaard

This study uses machine learning to analyze motor activity data from depressed patients and healthy controls, finding that a deep neural network achieves high accuracy in distinguishing between the groups.

PLoS ONE · Aug 24, 2020Peer-reviewedBioinformatics