A characteristic cerebellar biosignature for bipolar disorder, identified with fully automatic machine learning

A characteristic cerebellar biosignature for bipolar disorder, identified with fully automatic machine learning

Background: Transcriptomic profile differences between patients with bipolar disorder and healthy controls can be identified using machine learning and can provide information about the potential role of the cerebellum in the pathogenesis of bipolar disorder.With this aim, user-friendly, fully autom...

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Bibliographic Details
Main Authors: Georgios V. Thomaidis, Konstantinos Papadimitriou, Sotirios Michos, Evangelos Chartampilas, Ioannis Tsamardinos
Format: Article
Language:English
Published: Elsevier 2023-12-01
Series:IBRO Neuroscience Reports
Subjects:
Bipolar disorder
Biosignature
VEPH1
KREMEN2
RNU6–576 P
AutoML
Online Access:http://www.sciencedirect.com/science/article/pii/S2667242123000568

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http://www.sciencedirect.com/science/article/pii/S2667242123000568

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