Natural speech algorithm applied to baseline interview data can predict which patients will respond to psilocybin for treatment-resistant depression

Speech analytics and machine learning successfully differentiated depressed patients from healthy controls and identified treatment responders from non-responders with a significant level of 85% of accuracy (75% precision). Conclusions: Automatic natural language analysis was used to predict effective response to treatment with psilocybin, suggesting that these tools offer a highly cost-effective facility for screening individuals for treatment suitability and sensitivity. The sample size was small and replication is required to strengthen inferences on these results.

Read from original source

Entheogen-assisted Healing

Taking entheogens can be like air travel: people do it all the time, it’s usually fine, but when it’s not fine, it’s sometimes very bad. We’ve been there. And that’s where an experienced GUIDE can make the difference in the outcome.
I’m available by phone if you or someone you know wants to ask questions of ANY nature. Use this link to schedule a call HERE.