Machine learning helps predict schizophrenia treatment outcomes
2018
Chinese Academy of Sciences, Beijing, China
A machine learning algorithm is used to examine fMRI images of both newly diagnosed, previously untreated schizophrenia patients and healthy subjects. By measuring the connections of a brain region called the superior temporal cortex to other regions of the brain, the algorithm successfully identified patients with schizophrenia at 78 per cent accuracy. It also predicted with 82 per cent accuracy whether or not a patient would respond positively to a specific antipsychotic treatment named risperidone. The researchers hope to expand the work to include other mental illness such as major depressive and bipolar disorders.
Treatment response prediction and individualized identification of first-episode drug-naïve schizophrenia using brain functional connectivity
Xiang Yang Zhang
Added on: 07-06-2020
[1] https://www.nature.com/articles/s41380-018-0106-5[2] https://www.technologynetworks.com/informatics/news/machine-learning-helps-predict-schizophrenia-treatment-outcomes-306270
