Redisx, a machine learning approach, rationalizes rheumatoid arthritis and coronary artery disease patients uniquely upon identifying subpopulation differentiation markers from their genomic data

HIGHLIGHTS

• who: Daogang Guan and Hailong Zhu and Xuecheng Tai and Aiping Lu from the Oregon Health and Science University, United States have published the article: ReDisX, a machine learning approach, rationalizes rheumatoid arthritis and coronary artery disease patients uniquely upon identifying subpopulation differentiation markers from their genomic data, in the Journal: (JOURNAL)
• what: The authors have introduced ReDisX, a robust, scalable, and pathologically relevant computational framework to characterize the patients based on specific molecular-genetic signatures. The authors included RA patients, which are usually reported to have an immunological imbalance.
• how: The authors . . .
  

   

  

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