Extending schizophrenia diagnostic model to predict schizotypy in first-degree relatives.
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ABSTRACT:
SUBMITTER: Kalmady SV
PROVIDER: S-EPMC7648110 | biostudies-literature | 2020 Nov
REPOSITORIES: biostudies-literature
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Extending schizophrenia diagnostic model to predict schizotypy in first-degree relatives.
Kalmady Sunil Vasu SV Paul Animesh Kumar AK Greiner Russell R Agrawal Rimjhim R Amaresha Anekal C AC Shivakumar Venkataram V Narayanaswamy Janardhanan C JC Greenshaw Andrew J AJ Dursun Serdar M SM Venkatasubramanian Ganesan G
NPJ schizophrenia 20201106 1
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 imaging. In this study, we apply this learned model to first-degree relatives of schizophrenia patients, who were found to not have active psychosis or schizophrenia. We observe that the participants that ...[more]
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