Machine Learning Classifiers for Endometriosis Using Transcriptomics and Methylomics Data

Machine Learning Classifiers for Endometriosis Using Transcriptomics and Methylomics Data

Endometriosis is a complex and common gynecological disorder yet a poorly understood disease affecting about 176 million women worldwide and causing significant impact on their quality of life and economic burden. Neither a definitive clinical symptom nor a minimally invasive diagnostic method is av...

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Bibliographic Details
Main Authors: Sadia Akter, Dong Xu, Susan C. Nagel, John J. Bromfield, Katherine Pelch, Gilbert B. Wilshire, Trupti Joshi
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-09-01
Series:Frontiers in Genetics
Subjects:
endometriosis
machine learning
classification
methylomics
transcriptomics
DNA methylation
Online Access:https://www.frontiersin.org/article/10.3389/fgene.2019.00766/full

Internet

https://www.frontiersin.org/article/10.3389/fgene.2019.00766/full

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