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Researchers identified patients with schizophrenia with 78% accuracy through an automatic learning algorithm that they used to examine magnetic resonance imaging (MRI) images of newly diagnosed and untreated schizophrenic patients
. measuring the connections of a brain region called the temporal cortex greater than other brain regions, the algorithm also predicts with an accuracy of 82% whether a patient would respond positively to a specific antipsychotic treatment.
the first step, but ultimately we hope to find reliable biomarkers that can predict schizophrenia before symptoms appear, "said co-author Bo Cao of the University of Alberta in Canada.
"We also want to use the automatic learning treatment plan of a patient. That would not replace the doctor. In the future, with the aid of machine learning, if the doctor can select the best medicine or procedure for a specific patient at the first visit, that would be a good step forward, Cao added.
About one in 100 suggests a study published in the journal Molecular Psychiatry
. The current treatment of schizophrenia is still often determined by schizophrenia, a severe and disabling psychiatric disorder badociated with delusions, hallucinations, and cognitive impairment. a style of testing and error. If a medication does not work properly, the patient may suffer from prolonged symptoms and side effects, and miss the best time slot to control and treat the disease, they noted.
Source: IANS
Source of the Image: Shutterstock
Published: July 13, 2018 19:42
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