Machine Learning Helps Predict Instance & Treatment Outcomes Of Schizophrenia

Machine learning helps predict instances of, and treatment outcomes for, schizophrenia. In particular, people with recent-onset schizophrenia who are not taking pharmaceuticals for the condition (first-episode drug Naïve (FEDN)), can be identified with 78.6% accuracy. Their responses to antipsychotic drugs used to treat schizophrenia can be predicted with 82.5% accuracy.

These findings were reported in “Treatment Response Prediction And Individualized Identification Of First-Episode Drug-Naïve Schizophrenia Using Brain Functional Connectivity” by Bo Cao, Raymond Y. Cho, Dachun Chen, Meihong Xiu, Li Wang, Jair C. Soares, and Xiang Yang Zhang. The researchers recruited participants . . .