A recent study by Hyeon-Ho Hwang and team used EEG analysis to distinguish schizophrenia from bipolar disorder. They found that increased theta-scale entropy and power in schizophrenia can be detected with machine learning, achieving about 79% accuracy. This method highlights a promising use case for technology in mental health diagnostics.