Learning stable and predictive network-based patterns of schizophrenia and its clinical symptoms

@inproceedings{Gheiratmand2017LearningSA,
  title={Learning stable and predictive network-based patterns of schizophrenia and its clinical symptoms},
  author={M. Gheiratmand and Irina Rish and Guillermo A. Cecchi and Matthew R. G. Brown and Russell Greiner and Pablo I. Polosecki and Pouya Bashivan and Andrew J. Greenshaw and Rajamannar Ramasubbu and Serdar M. Dursun},
  booktitle={npj Schizophrenia},
  year={2017}
}
Schizophrenia is often associated with disrupted brain connectivity. However, identifying specific neuroimaging-based patterns pathognomonic for schizophrenia and related symptom severity remains a challenging open problem requiring large-scale data-driven analyses emphasizing not only statistical significance but also stability across multiple datasets, contexts and cohorts. Accurate prediction on previously unseen subjects, or generalization, is also essential for any useful biomarker of… CONTINUE READING
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Proceedings of the National Academy of Sciences of the United States of America • 2016
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