Extending schizophrenia diagnostic model to predict schizotypy in first-degree relatives

Recently, we developed a machine-learning algorithm “EMPaSchiz” that learns, from a training set of schizophrenia patients and healthy individuals, a model that predicts if a novel individual has schizophrenia, based on features extracted from his/her resting-state functional magnetic resonance imag...

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Detalles Bibliográficos
Autores principales: Kalmady, Sunil Vasu, Paul, Animesh Kumar, Greiner, Russell, Agrawal, Rimjhim, Amaresha, Anekal C., Shivakumar, Venkataram, Narayanaswamy, Janardhanan C., Greenshaw, Andrew J., Dursun, Serdar M., Venkatasubramanian, Ganesan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Brief Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7648110/
https://www.ncbi.nlm.nih.gov/pubmed/33159092
http://dx.doi.org/10.1038/s41537-020-00119-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7648110/
https://www.ncbi.nlm.nih.gov/pubmed/33159092
http://dx.doi.org/10.1038/s41537-020-00119-y

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